Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018最新文献
Kentaro Ino, Naoto Ienaga, Yuta Sugiura, H. Saito, N. Miyata, M. Tada
Recently, there has been an increase in research estimating hand poses using images. Due to the hand’s high degree of freedom and self-occlusion, multi-view or depth images are often used. Our objective was to estimate hand poses specifically while grasping objects. When holding something, the hand moves in many directions. However, if the camera is too distant from the hand, it may move out of range. Widening the viewing angle, however, reduces the resolution beyond usable limits. One possible solution was developed by Kashiwagi by setting the camera on an object, the hand’s pose can be estimated regardless of its position. However, Kashiwagi's method cannot be used without estimating the fingertips’ positions. Recently, another method using a convolutional neural network (CNN), useful for estimating complex poses, has been proposed. Unfortunately, it is difficult to collect the large number of images with ground truth needed for learning. In this research, we focused on creating a large dataset by generating hand pose images using a digital human model and motioncaptured data using DhaibaWorks. We evaluated the model by calculating the distance of the estimated pose and ground truth of the test data, which was approximately 12.3 mm on average. In comparison, the average distance in related work was 18.5 mm. We also tested our method with ordinary camera images and confirmed that it can be used in the real world. Our method provides a new means of dataset generation: annotations are done automatically with motion capture technology, which reduces the time required. In future work, we will improve the architecture of the CNN and shorten the execution time for real-time processing.
{"title":"Grasping Hand Pose Estimation from RGB Images Using Digital Human Model by Convolutional Neural Network","authors":"Kentaro Ino, Naoto Ienaga, Yuta Sugiura, H. Saito, N. Miyata, M. Tada","doi":"10.15221/18.154","DOIUrl":"https://doi.org/10.15221/18.154","url":null,"abstract":"Recently, there has been an increase in research estimating hand poses using images. Due to the hand’s high degree of freedom and self-occlusion, multi-view or depth images are often used. Our objective was to estimate hand poses specifically while grasping objects. When holding something, the hand moves in many directions. However, if the camera is too distant from the hand, it may move out of range. Widening the viewing angle, however, reduces the resolution beyond usable limits. One possible solution was developed by Kashiwagi by setting the camera on an object, the hand’s pose can be estimated regardless of its position. However, Kashiwagi's method cannot be used without estimating the fingertips’ positions. Recently, another method using a convolutional neural network (CNN), useful for estimating complex poses, has been proposed. Unfortunately, it is difficult to collect the large number of images with ground truth needed for learning. In this research, we focused on creating a large dataset by generating hand pose images using a digital human model and motioncaptured data using DhaibaWorks. We evaluated the model by calculating the distance of the estimated pose and ground truth of the test data, which was approximately 12.3 mm on average. In comparison, the average distance in related work was 18.5 mm. We also tested our method with ordinary camera images and confirmed that it can be used in the real world. Our method provides a new means of dataset generation: annotations are done automatically with motion capture technology, which reduces the time required. In future work, we will improve the architecture of the CNN and shorten the execution time for real-time processing.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126597873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Haßmann, Seraphina Stoeger, Jacqueline Dastl, W. Krach
3D scanning technology is widely used in medical and clothing applications as well as research projects. This paper presents our experiences with a low-cost hand-held 1st generation SenseTM 3D scanner (3D Systems Inc., Rock Hill, SC, USA) including free software Sense (V2.2) [1]. The shape of the female torso, including breast tissue volume, was determined using 3D surface scans. Female upper body area implies special requirements for positioning of participant and handling of scanner to gain good scan quality for reliable surface geometry. Lighting, settings and options, advantages and drawbacks of this scanner, including dimensional tolerance and repeatability measurements using mannequin and human body are addressed. Data processing and anonymization issues in the included free software are shown. Dimensional accuracy has to be proven first before using the SenseTM 3D scanner. For this purpose, a rigid plastic mannequin with markups, so-called fiducial points, was used. The distance from incisura jugularis to umbilicus height and nipple distance were measured using manual anthropometry compasses and virtual measurement from the 3D scan. The deviation was 0.1 % and -0.03 %, respectively. Repeatability of measurements was determined calculating average error parameter from 5 scans in standing and supine position (lying on the back) using the alignment procedure in MeshLab (v1.3.4BETA) [2]. Mean average error was 0.26 mm for both standing and supine position using either 4 or 19 pairs of points for alignment. Keeping in mind that the scanner is optimized for human skin and not for plastic surface, which sometimes causes reflections, this deviation can be judged very low. In addition, repeatability measurements were carried out on 3 pilot study participants. Mean average error for all participants and positions was 1.33 mm. Compared to the element size of maximum 3 mm this error is acceptable. Hence, the low-cost SenseTM scanner can be used in research projects dealing with human body geometric measurements.
3D扫描技术广泛应用于医疗和服装应用以及研究项目。本文介绍了我们使用低成本手持式第一代SenseTM 3D扫描仪(3D Systems Inc.， Rock Hill, SC, USA)的经验，包括免费软件Sense (V2.2)[1]。女性躯干的形状，包括乳房组织的体积，是通过3D表面扫描确定的。女性上半身区域对参与者的定位和扫描仪的处理有特殊要求，以获得可靠的表面几何形状的良好扫描质量。该扫描仪的照明、设置和选项、优点和缺点，包括使用人体模型和人体的尺寸公差和可重复性测量。所包含的免费软件中的数据处理和匿名化问题显示。在使用SenseTM 3D扫描仪之前，必须首先验证尺寸精度。为此，使用了带有标记的刚性塑料人体模型，即所谓的基准点。采用手工人体测量圆规和三维扫描虚拟测量法测量颈切牙至脐高度的距离和乳头距离。偏差分别为0.1%和- 0.03%。使用MeshLab (v1.3.4BETA)中的校准程序计算站立和仰卧位(仰卧位)5次扫描的平均误差参数，以确定测量的重复性[2]。使用4对或19对点进行对齐时，站立和仰卧位置的平均误差为0.26 mm。请记住，扫描仪是针对人体皮肤而不是塑料表面进行优化的，塑料表面有时会引起反射，因此可以判断这种偏差非常低。此外，对3名试点研究参与者进行了重复性测量。所有参与者和位置的平均误差为1.33 mm。与最大3毫米的元件尺寸相比，这个误差是可以接受的。因此，低成本的SenseTM扫描仪可用于处理人体几何测量的研究项目。
{"title":"Scanning Procedure of Female Torso Using Low-Cost Hand-Held Sense 3D Scanner","authors":"M. Haßmann, Seraphina Stoeger, Jacqueline Dastl, W. Krach","doi":"10.15221/18.074","DOIUrl":"https://doi.org/10.15221/18.074","url":null,"abstract":"3D scanning technology is widely used in medical and clothing applications as well as research projects. This paper presents our experiences with a low-cost hand-held 1st generation SenseTM 3D scanner (3D Systems Inc., Rock Hill, SC, USA) including free software Sense (V2.2) [1]. The shape of the female torso, including breast tissue volume, was determined using 3D surface scans. Female upper body area implies special requirements for positioning of participant and handling of scanner to gain good scan quality for reliable surface geometry. Lighting, settings and options, advantages and drawbacks of this scanner, including dimensional tolerance and repeatability measurements using mannequin and human body are addressed. Data processing and anonymization issues in the included free software are shown. Dimensional accuracy has to be proven first before using the SenseTM 3D scanner. For this purpose, a rigid plastic mannequin with markups, so-called fiducial points, was used. The distance from incisura jugularis to umbilicus height and nipple distance were measured using manual anthropometry compasses and virtual measurement from the 3D scan. The deviation was 0.1 % and -0.03 %, respectively. Repeatability of measurements was determined calculating average error parameter from 5 scans in standing and supine position (lying on the back) using the alignment procedure in MeshLab (v1.3.4BETA) [2]. Mean average error was 0.26 mm for both standing and supine position using either 4 or 19 pairs of points for alignment. Keeping in mind that the scanner is optimized for human skin and not for plastic surface, which sometimes causes reflections, this deviation can be judged very low. In addition, repeatability measurements were carried out on 3 pilot study participants. Mean average error for all participants and positions was 1.33 mm. Compared to the element size of maximum 3 mm this error is acceptable. Hence, the low-cost SenseTM scanner can be used in research projects dealing with human body geometric measurements.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"432 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123213381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Susan L. Sokolowski, Linsey Griffin, S. Chandrasekhar
Historically, three methods have been used to collect hand anthropometric data. The oldest and most known method was developed in the late 1800’s, where researchers used rulers, calipers and tape measures to manually collect data from a subject’s landmarked hand, or from obvious parts of the limb that can be measured without landmarks (e.g., wrist circumference). The second method uses 2D imagery that is collected from the subject and then measured manually/digitally with rulers or calipers. A variety of devices can collect this type of imagery; including photo boxes, x-ray machines, flatbed scanners and photo copiers. These tools are convenient for collecting hand data, but can be limiting as they only collect one flat view of the hand, at one time. Over the last ten years, 3D scanning technology has been adopted for hand studies because of its’ ability to collect data quickly, and with better accuracy, as there are less steps and human error involved. 3D scanning allows researchers to collect data of an entire body part at one time, where it can be analyzed digitally beyond straight measures and circumferences. There are three types of scanners available in the market to collect hand anthropometric data, they include: 1) ones made specifically for hand scanning, 2) foot scanners and 3) hand held/mobile/tablet devices. But which 3D scanner should you select for your hand research? This can be an overwhelming decision, as there are so many options, and knowing what to look for can be confusing and quite difficult to find. Through experimentation with different equipment and hand studies, the researchers, developed a framework of key attributes that are important to selecting 3D scanners. They include: vendor/location, hand-held compatibility, scanner size, weight, envelope, supporting weight, price; along with scanner technology, timing, resolution, color capture, and file saving. Through this research, the authors desire to help others who want to purchase and conduct hand anthropometric research, to be more informed so can use their resources effectively and efficiently to have success with their work.
{"title":"Current Technology Landscape for Collecting Hand Anthropometric Data","authors":"Susan L. Sokolowski, Linsey Griffin, S. Chandrasekhar","doi":"10.15221/18.142","DOIUrl":"https://doi.org/10.15221/18.142","url":null,"abstract":"Historically, three methods have been used to collect hand anthropometric data. The oldest and most known method was developed in the late 1800’s, where researchers used rulers, calipers and tape measures to manually collect data from a subject’s landmarked hand, or from obvious parts of the limb that can be measured without landmarks (e.g., wrist circumference). The second method uses 2D imagery that is collected from the subject and then measured manually/digitally with rulers or calipers. A variety of devices can collect this type of imagery; including photo boxes, x-ray machines, flatbed scanners and photo copiers. These tools are convenient for collecting hand data, but can be limiting as they only collect one flat view of the hand, at one time. Over the last ten years, 3D scanning technology has been adopted for hand studies because of its’ ability to collect data quickly, and with better accuracy, as there are less steps and human error involved. 3D scanning allows researchers to collect data of an entire body part at one time, where it can be analyzed digitally beyond straight measures and circumferences. There are three types of scanners available in the market to collect hand anthropometric data, they include: 1) ones made specifically for hand scanning, 2) foot scanners and 3) hand held/mobile/tablet devices. But which 3D scanner should you select for your hand research? This can be an overwhelming decision, as there are so many options, and knowing what to look for can be confusing and quite difficult to find. Through experimentation with different equipment and hand studies, the researchers, developed a framework of key attributes that are important to selecting 3D scanners. They include: vendor/location, hand-held compatibility, scanner size, weight, envelope, supporting weight, price; along with scanner technology, timing, resolution, color capture, and file saving. Through this research, the authors desire to help others who want to purchase and conduct hand anthropometric research, to be more informed so can use their resources effectively and efficiently to have success with their work.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117324971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anke Klepser, S. Hiss, A. Mahr-Erhardt, S. Morlock
Fashion garments sculpt the human body according to the up-to-date style. Foundation garments used to be out of whalebone and stiff materials. Nowadays thin and light shapewear aims to smooth obvious subcutaneous fat. Material, pattern, fit and formability of the body tissue influence the effect of shapewear. Thus, it is not known how much or even if shaping garments effect the body form. Moreover, there is a lack of standardized methods to analyze shaping effects of foundation garments. Up to now research focused two paths to analyze the functionality of shaping garment. First was to quantify the pressure applied, second was to measure the body changes achieved by the products. Governmental funded research project “Shaping Effects” aims to combine and pursue the research approaches. Project term is two years starting from April 2017. Therefore, most of the work is ongoing. The following presents preliminary results. 41 shapewear products were tested with HOSY apparatus to measure pressure gradient. PicoPress device was utilized to determine pressure between garment and manikin or human body respectively. 3D-analysis based on before and after scans was performed to measure changes in body geometry. Two test subjects tested shaping garments so far. Test methods were processed successfully. First results underlined the influence of material properties, body geometry and body tissue on shaping effects.
{"title":"Three-Dimensional Quantification of Foundation Garment s Shaping Effects","authors":"Anke Klepser, S. Hiss, A. Mahr-Erhardt, S. Morlock","doi":"10.15221/18.092","DOIUrl":"https://doi.org/10.15221/18.092","url":null,"abstract":"Fashion garments sculpt the human body according to the up-to-date style. Foundation garments used to be out of whalebone and stiff materials. Nowadays thin and light shapewear aims to smooth obvious subcutaneous fat. Material, pattern, fit and formability of the body tissue influence the effect of shapewear. Thus, it is not known how much or even if shaping garments effect the body form. Moreover, there is a lack of standardized methods to analyze shaping effects of foundation garments. Up to now research focused two paths to analyze the functionality of shaping garment. First was to quantify the pressure applied, second was to measure the body changes achieved by the products. Governmental funded research project “Shaping Effects” aims to combine and pursue the research approaches. Project term is two years starting from April 2017. Therefore, most of the work is ongoing. The following presents preliminary results. 41 shapewear products were tested with HOSY apparatus to measure pressure gradient. PicoPress device was utilized to determine pressure between garment and manikin or human body respectively. 3D-analysis based on before and after scans was performed to measure changes in body geometry. Two test subjects tested shaping garments so far. Test methods were processed successfully. First results underlined the influence of material properties, body geometry and body tissue on shaping effects.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115197329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haining Wang, Wenxiu Yang, Yang Yu, Wanrong Chen, R. Ball
Abstract SizeChina-Hunan collects the latest data of Chinese head and face which will provide critical information for ergonomics. The accurate figure of the human head and face can provide vital advantages by designing wearable products, such as virtual reality (VR) and augmented reality (AR) headsets or safety glasses. However, the complex surface geometry of the human head and face presents a challenge for designers and engineers on account of the traditional ways of anthropometric surveys has numbers of limitations. The anthropometric survey of SizeChina-Hunan makes a combination of the traditional measurement way and high-resolution 3D scanning. The total number of subjects required at each site recruit 275 subjects with individuals ranging in age from 18 to 70 years and two sexes. Consequently, the goal was to recruit 2200 individuals totally ranging in 7 regional location respectively.
{"title":"3D Digital Anthropometric Study on Chinese Head and Face","authors":"Haining Wang, Wenxiu Yang, Yang Yu, Wanrong Chen, R. Ball","doi":"10.15221/18.287","DOIUrl":"https://doi.org/10.15221/18.287","url":null,"abstract":"Abstract SizeChina-Hunan collects the latest data of Chinese head and face which will provide critical information for ergonomics. The accurate figure of the human head and face can provide vital advantages by designing wearable products, such as virtual reality (VR) and augmented reality (AR) headsets or safety glasses. However, the complex surface geometry of the human head and face presents a challenge for designers and engineers on account of the traditional ways of anthropometric surveys has numbers of limitations. The anthropometric survey of SizeChina-Hunan makes a combination of the traditional measurement way and high-resolution 3D scanning. The total number of subjects required at each site recruit 275 subjects with individuals ranging in age from 18 to 70 years and two sexes. Consequently, the goal was to recruit 2200 individuals totally ranging in 7 regional location respectively.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131450347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Takumi Kobayashi, Naoto Ienaga, Yuta Sugiura, H. Saito, N. Miyata, M. Tada
In recent years, online purchasing of clothes and shoes has become increasingly common. Although this is convenient, it can be difficult to choose the correct shoe size. While 3D foot scanners can accurately measure foot size and shape, this expensive and large scale equipment is not generally accessible for personal use, and there is a need for some simple and accurate means of measuring the foot in 3D. Recently developed smartphones with depth cameras enable easier measurement of 3D shapes, and this paper describes a method for measuring foot shape using a 3D point cloud captured from multiple directions by such a camera. As a 3D point cloud can potentially include noise or may omit occluded parts of the foot, we propose the use of a dataset of 3D foot shapes collected by a precise 3D shape scanner. We show how a deformable model can be generated by performing a principal component analysis on this dataset, minimizing error to recover a complete and high-accuracy 3D profile of the entire foot. We tested this method by comparing the 3D shape so produced to the 3D shape measured by the 3D scanner. The proposed method was found to scan foot shape with an error of about 1.13 mm. As demonstrated experimentally, the contribution of our work is in introducing the deformable model of 3D foot shapes based on principal component analysis, so that accurate shape models can be calculated from noisy and occluded 3D point clouds obtained via smartphone input.
{"title":"A Simple 3D Scanning System of the Human Foot Using a Smartphone with a Depth Camera","authors":"Takumi Kobayashi, Naoto Ienaga, Yuta Sugiura, H. Saito, N. Miyata, M. Tada","doi":"10.15221/18.161","DOIUrl":"https://doi.org/10.15221/18.161","url":null,"abstract":"In recent years, online purchasing of clothes and shoes has become increasingly common. Although this is convenient, it can be difficult to choose the correct shoe size. While 3D foot scanners can accurately measure foot size and shape, this expensive and large scale equipment is not generally accessible for personal use, and there is a need for some simple and accurate means of measuring the foot in 3D. Recently developed smartphones with depth cameras enable easier measurement of 3D shapes, and this paper describes a method for measuring foot shape using a 3D point cloud captured from multiple directions by such a camera. As a 3D point cloud can potentially include noise or may omit occluded parts of the foot, we propose the use of a dataset of 3D foot shapes collected by a precise 3D shape scanner. We show how a deformable model can be generated by performing a principal component analysis on this dataset, minimizing error to recover a complete and high-accuracy 3D profile of the entire foot. We tested this method by comparing the 3D shape so produced to the 3D shape measured by the 3D scanner. The proposed method was found to scan foot shape with an error of about 1.13 mm. As demonstrated experimentally, the contribution of our work is in introducing the deformable model of 3D foot shapes based on principal component analysis, so that accurate shape models can be calculated from noisy and occluded 3D point clouds obtained via smartphone input.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130698609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Gill, Yuting Wang, Maryam Ahmed, S. Hayes, A. Harwood, James Gill
Body scanning provides one of the most efficient tools for recording information of the human body to support the development of body worn products. Traditionally the construction of garment patterns uses manual measurements and during the construction process applies some proportions, to create a pattern block [1], [2]. Traditional methods of drafting pattern blocks (slopers) apply very limited data from the body compared to the areas they cover and subsequently often require post drafting adjustments to achieve a suitable fit. Most pattern books have guidance on adjustments to blocks to accommodate figure variations [3]–[5]. These methods of block construction are well established and understood and have been used to inspire new approaches and propose theories for pattern block development [2], [6]. With advances in body scanning it is now possible to generate more measurements allowing for the body to have greater context in the process of pattern construction. This research retains the established 2D drafting methods and looks to explore further measurements than those traditionally used to create pattern blocks, these resulting blocks could then better reflect the individual variations in potential wearer size, shape and proportion. As well as looking to determine suitable measurements from a Size Stream (SS14) body scanner to inform the development of pattern blocks, this research tests an established skirt draft [4] using scan measurements, against a newly developed skirt drafting method which utilises the measurement capabilities of body scanning. The developed patterns are each tested on five dress forms. As well as assessing the resulting patterns, recommendations are made regarding how body scanning can be used to better inform pattern construction methods. This includes a contribution toward the theories of pattern construction, which will allow greater exploitation of body scanning technologies in developing better fitting and functioning garments. This research shows one means by which body scanning technologies can help to bridge the gap between traditional techniques of creating pattern blocks and the promising opportunities presented by body scanning technologies.
{"title":"Scan to Pattern: How Body Scanning Can Help Transform Traditional Methods of Creating Pattern Blocks","authors":"S. Gill, Yuting Wang, Maryam Ahmed, S. Hayes, A. Harwood, James Gill","doi":"10.15221/18.236","DOIUrl":"https://doi.org/10.15221/18.236","url":null,"abstract":"Body scanning provides one of the most efficient tools for recording information of the human body to support the development of body worn products. Traditionally the construction of garment patterns uses manual measurements and during the construction process applies some proportions, to create a pattern block [1], [2]. Traditional methods of drafting pattern blocks (slopers) apply very limited data from the body compared to the areas they cover and subsequently often require post drafting adjustments to achieve a suitable fit. Most pattern books have guidance on adjustments to blocks to accommodate figure variations [3]–[5]. These methods of block construction are well established and understood and have been used to inspire new approaches and propose theories for pattern block development [2], [6]. With advances in body scanning it is now possible to generate more measurements allowing for the body to have greater context in the process of pattern construction. This research retains the established 2D drafting methods and looks to explore further measurements than those traditionally used to create pattern blocks, these resulting blocks could then better reflect the individual variations in potential wearer size, shape and proportion. As well as looking to determine suitable measurements from a Size Stream (SS14) body scanner to inform the development of pattern blocks, this research tests an established skirt draft [4] using scan measurements, against a newly developed skirt drafting method which utilises the measurement capabilities of body scanning. The developed patterns are each tested on five dress forms. As well as assessing the resulting patterns, recommendations are made regarding how body scanning can be used to better inform pattern construction methods. This includes a contribution toward the theories of pattern construction, which will allow greater exploitation of body scanning technologies in developing better fitting and functioning garments. This research shows one means by which body scanning technologies can help to bridge the gap between traditional techniques of creating pattern blocks and the promising opportunities presented by body scanning technologies.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123627236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
From the aspect of breathing movement, this paper takes the singer of the female singing as the object of the study, which is focus on the research of the body breath status of performers before and after wearing tunic dresses. Then analysis the relationship between performer’s breathing movement and dress comfort. Base on this, the 3DCaMega human body scanning system is used to obtain the point cloud data of the performers in the same state to establish the virtual human body model and according to the model data and comfortable level. CLO3D is utilized to optimize the structure of tunic fitting. Finally, CLO3D is used to simulate the fitting and to prove the comfort of the tunic dress,Making sure performers can gain excellent artistic singing effects.
{"title":"The Design of Vocal Performance Dress Based on 3D Technology","authors":"Zifei Li, Wei Xiong, Li Zhou","doi":"10.15221/18.264","DOIUrl":"https://doi.org/10.15221/18.264","url":null,"abstract":"From the aspect of breathing movement, this paper takes the singer of the female singing as the object of the study, which is focus on the research of the body breath status of performers before and after wearing tunic dresses. Then analysis the relationship between performer’s breathing movement and dress comfort. Base on this, the 3DCaMega human body scanning system is used to obtain the point cloud data of the performers in the same state to establish the virtual human body model and according to the model data and comfortable level. CLO3D is utilized to optimize the structure of tunic fitting. Finally, CLO3D is used to simulate the fitting and to prove the comfort of the tunic dress,Making sure performers can gain excellent artistic singing effects.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115745383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Audrey Cheong, S. Hanson, G. Reece, M. Markey, F. Merchant
Autologous fat grafting is increasingly employed to address volume asymmetry and contour irregularity following breast reconstruction for breast cancer. However, there are no well-established objective tools to accurately measure change in graft volume and breast shape over time. Three-dimensional (3D) surface imaging allows for objective analysis of changes in breast shape and size, which clinicians and researchers can use to evaluate the effects of fat grafting. This study presents several measurements (Gaussian curvature, shape index, surface orientation, and volume) that can be extracted from 3D surface images of patients. These measurements are demonstrated on three patients (two patients after implant reconstruction and one after bilateral mastopexy) before and after fat grafting. The results of this study can help pave the way for clinicians and researchers to develop standardized metrics for objectively evaluating fat graft processing techniques. Using the proposed measurements, we were able to evaluate key shape and size differences in the 3D surface images before and after fat grafting.
{"title":"Potential of 3D Surface Imaging for Quantitative Analysis of Fat Grafting","authors":"Audrey Cheong, S. Hanson, G. Reece, M. Markey, F. Merchant","doi":"10.15221/18.057","DOIUrl":"https://doi.org/10.15221/18.057","url":null,"abstract":"Autologous fat grafting is increasingly employed to address volume asymmetry and contour irregularity following breast reconstruction for breast cancer. However, there are no well-established objective tools to accurately measure change in graft volume and breast shape over time. Three-dimensional (3D) surface imaging allows for objective analysis of changes in breast shape and size, which clinicians and researchers can use to evaluate the effects of fat grafting. This study presents several measurements (Gaussian curvature, shape index, surface orientation, and volume) that can be extracted from 3D surface images of patients. These measurements are demonstrated on three patients (two patients after implant reconstruction and one after bilateral mastopexy) before and after fat grafting. The results of this study can help pave the way for clinicians and researchers to develop standardized metrics for objectively evaluating fat graft processing techniques. Using the proposed measurements, we were able to evaluate key shape and size differences in the 3D surface images before and after fat grafting.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128266342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pawel Liberadzki, Lukasz Markiewicz, M. Witkowski, R. Sitnik
One of the drawbacks of the traditional 3D whole body scanning is that it is capable of capturing only static models. In most of the cases it is impossible to properly analyze the way people move as they are not able to freeze their movement for a certain amount of time. In order to add a 4th dimension (time) to measurements, a system have to be built using stable ultra-fast 3D scanners. The presented solution meets industrial requirements for 4D measurements of dynamic objects. It is capable of acquiring up to 120 Hz sequences of high precision point clouds along with an information about its lightness and normal vectors. A spatial resolution of 1 mm is obtained with an inaccuracy below 0.5 mm. It was originally designed for a 4D human body shape measurement to support medical rehabilitation monitoring, however it is not restricted to this application. The system is composed of four directional measurement columns [1]. Sufficient body surface coverage is possible thanks to an even distribution of modules, each consisting of 1 projector and 2 detectors – on the upper and lower part of the head. Their working principle is based on a structured light projection, specifically a single frame pattern approach which enabled achievement of the declared frequency. For this particular case a problem of synchronization (highly erroneous overlapping of the projected patterns) was solved. A sine modulated patterns are colored and distinguished using a spectral separation via color filters. Information about fringe numbers is encoded using an additional transverse modulation of the patterns. Retrieval of a single multidirectional output cloud is done using a set of dedicated algorithms, including phase unwrapping on a single image per detector, scaling into XYZ coordinates and common calibration. The high precision 4D data is very heavy. A raw 1 minute of 120 Hz scan requires around 360 GB of a disk space. In order to handle such data, the specialized software called FRAMES (Framework and Robust Algorithms for Models of Extreme Size) was developed. It has built-in 4D RAM (Random Access Memory) manager which enables efficient visualization, advanced multithread processing and analysis of such data. The presented 4D scanning solution was tested in a real-life environment. The possibility of performing 3D body scanning in time enabled the rehabilitation progress monitoring after leg amputation.
{"title":"Novel 4D Whole Body Scanning Solution and its Medical Application","authors":"Pawel Liberadzki, Lukasz Markiewicz, M. Witkowski, R. Sitnik","doi":"10.15221/18.047","DOIUrl":"https://doi.org/10.15221/18.047","url":null,"abstract":"One of the drawbacks of the traditional 3D whole body scanning is that it is capable of capturing only static models. In most of the cases it is impossible to properly analyze the way people move as they are not able to freeze their movement for a certain amount of time. In order to add a 4th dimension (time) to measurements, a system have to be built using stable ultra-fast 3D scanners. The presented solution meets industrial requirements for 4D measurements of dynamic objects. It is capable of acquiring up to 120 Hz sequences of high precision point clouds along with an information about its lightness and normal vectors. A spatial resolution of 1 mm is obtained with an inaccuracy below 0.5 mm. It was originally designed for a 4D human body shape measurement to support medical rehabilitation monitoring, however it is not restricted to this application. The system is composed of four directional measurement columns [1]. Sufficient body surface coverage is possible thanks to an even distribution of modules, each consisting of 1 projector and 2 detectors – on the upper and lower part of the head. Their working principle is based on a structured light projection, specifically a single frame pattern approach which enabled achievement of the declared frequency. For this particular case a problem of synchronization (highly erroneous overlapping of the projected patterns) was solved. A sine modulated patterns are colored and distinguished using a spectral separation via color filters. Information about fringe numbers is encoded using an additional transverse modulation of the patterns. Retrieval of a single multidirectional output cloud is done using a set of dedicated algorithms, including phase unwrapping on a single image per detector, scaling into XYZ coordinates and common calibration. The high precision 4D data is very heavy. A raw 1 minute of 120 Hz scan requires around 360 GB of a disk space. In order to handle such data, the specialized software called FRAMES (Framework and Robust Algorithms for Models of Extreme Size) was developed. It has built-in 4D RAM (Random Access Memory) manager which enables efficient visualization, advanced multithread processing and analysis of such data. The presented 4D scanning solution was tested in a real-life environment. The possibility of performing 3D body scanning in time enabled the rehabilitation progress monitoring after leg amputation.","PeriodicalId":416022,"journal":{"name":"Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130508673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Proceedings of 3DBODY.TECH 2018 - 9th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018
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