Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464181
Monika Arora, M. Dutta, C. Travieso-González, Radim Burget
Apples are one of the most common fruit on the planet. It is rich in iron, fiber, antioxidants and other nutritive quality; which are incredibly important for human body and brain. The quality of an apple gets affected once they are chopped. This paper presents a non-destructive image processing based algorithm that identifies the presence of enzymatic browning in chopped apples for the determination of its nutrients loss. The proposed imperative assemblage of this image processing algorithm makes it flexible, automatic and non-destructive. The quantification of enzymatic browning in chopped apples has been obtained with high precision using this proposed imaging based method. The machine learning based on strategic selection of discriminatory statistical features of chopped apples extracted in wavelet domain makes it a novel approach. 85% of accuracy has been achieved by using machine learning based Support Vector Machine (SVM) classifier.
{"title":"Image Processing Based Classification of Enzymatic Browning in Chopped Apples","authors":"Monika Arora, M. Dutta, C. Travieso-González, Radim Burget","doi":"10.1109/IWOBI.2018.8464181","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464181","url":null,"abstract":"Apples are one of the most common fruit on the planet. It is rich in iron, fiber, antioxidants and other nutritive quality; which are incredibly important for human body and brain. The quality of an apple gets affected once they are chopped. This paper presents a non-destructive image processing based algorithm that identifies the presence of enzymatic browning in chopped apples for the determination of its nutrients loss. The proposed imperative assemblage of this image processing algorithm makes it flexible, automatic and non-destructive. The quantification of enzymatic browning in chopped apples has been obtained with high precision using this proposed imaging based method. The machine learning based on strategic selection of discriminatory statistical features of chopped apples extracted in wavelet domain makes it a novel approach. 85% of accuracy has been achieved by using machine learning based Support Vector Machine (SVM) classifier.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130810298","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}
Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464139
N. Strisciuglio, María Leyva-Vallina, N. Petkov, R. Muñoz-Salinas
In this paper, we present an outdoor monocular camera localization system based on artificial markers and test its performance in one of the test gardens of the TrimBot2020 project, in Wageningen. We use ArUco markers to construct a map of the environment and to subsequently localize the camera position within it. We combine the localization algorithm based on ArUco with a Kalman filter to smooth the trajectory and improve the localization stability with respect to fast movements of the camera, and blurred or noisy images. We recorded two sequences, with resolution 480p and l080p respectively, in the TrimBot2020 garden. We compare the localization performance of ArUco with a keypoint-based approach, namely ORB-SLAM2. We analyze and discuss the strengths and problems of both marker- and keypoint-based approaches on the considered sequences. The performed comparison suggests that the two approaches might be fused to jointly improve re-localization and reduce the drift in pose estimation.
{"title":"Camera Localization in Outdoor Garden Environments Using Artificial Landmarks","authors":"N. Strisciuglio, María Leyva-Vallina, N. Petkov, R. Muñoz-Salinas","doi":"10.1109/IWOBI.2018.8464139","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464139","url":null,"abstract":"In this paper, we present an outdoor monocular camera localization system based on artificial markers and test its performance in one of the test gardens of the TrimBot2020 project, in Wageningen. We use ArUco markers to construct a map of the environment and to subsequently localize the camera position within it. We combine the localization algorithm based on ArUco with a Kalman filter to smooth the trajectory and improve the localization stability with respect to fast movements of the camera, and blurred or noisy images. We recorded two sequences, with resolution 480p and l080p respectively, in the TrimBot2020 garden. We compare the localization performance of ArUco with a keypoint-based approach, namely ORB-SLAM2. We analyze and discuss the strengths and problems of both marker- and keypoint-based approaches on the considered sequences. The performed comparison suggests that the two approaches might be fused to jointly improve re-localization and reduce the drift in pose estimation.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133639786","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}
Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464188
Alen Selimović, Blaž Meden, P. Peer, A. Hladnik
Content-aware compression based on the use of saliency maps aims to improve the interpretability of an image by encoding the more relevant image regions with a higher quality than the rest of the image. This paper revisits two convolutional neural network (CNN) models based on VGG16, multi-structure region of interest (MS-ROI) and class activation map (CAM), which enable the localization of salient image regions. While the MS-ROI model allows for the localization of multiple salient image regions, the CAM model, on the other hand, tends to localize only the most relevant class. We use the contextual information provided by the obtained saliency maps to guide the compression. By encoding more important image regions at a higher bitrate and less important ones at a lower bitrate, different qualities of compression for the regions of interest and the background are obtained, while also achieving smooth transitions from salient to non-salient regions. The performance of both models is evaluated on images from the MIT Saliency Benchmark dataset and the General-100 dataset, and the results of the compression are compared to the standard JPEG compression at different quality factors. Experimental results show that for the files of approximately same size, the compression methods based on the two CNN models outperform the standard JPEG compression. When comparing the compression based on the MS-ROI model to the compression based on the CAM model, the former is characterized by a higher PSNR and a better visual quality of the obtained images.
{"title":"Analysis of Content-Aware Image Compression with VGG16","authors":"Alen Selimović, Blaž Meden, P. Peer, A. Hladnik","doi":"10.1109/IWOBI.2018.8464188","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464188","url":null,"abstract":"Content-aware compression based on the use of saliency maps aims to improve the interpretability of an image by encoding the more relevant image regions with a higher quality than the rest of the image. This paper revisits two convolutional neural network (CNN) models based on VGG16, multi-structure region of interest (MS-ROI) and class activation map (CAM), which enable the localization of salient image regions. While the MS-ROI model allows for the localization of multiple salient image regions, the CAM model, on the other hand, tends to localize only the most relevant class. We use the contextual information provided by the obtained saliency maps to guide the compression. By encoding more important image regions at a higher bitrate and less important ones at a lower bitrate, different qualities of compression for the regions of interest and the background are obtained, while also achieving smooth transitions from salient to non-salient regions. The performance of both models is evaluated on images from the MIT Saliency Benchmark dataset and the General-100 dataset, and the results of the compression are compared to the standard JPEG compression at different quality factors. Experimental results show that for the files of approximately same size, the compression methods based on the two CNN models outperform the standard JPEG compression. When comparing the compression based on the MS-ROI model to the compression based on the CAM model, the former is characterized by a higher PSNR and a better visual quality of the obtained images.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125954878","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}
Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464218
G. Wachs-Lopes, Fernanda S. Beltrame, R. M. Santos, P. Rodrigues
As new technological challenges depending on the computational performance of bio-inspired algorithms emerge, the demand for more efficient heuristic solutions grows up at same rate. Specifically, the medical field is one of the most challenging, due to the fact of the pre-processing steps, such as multilevel segmentation of color spaces, require greater precision. Thus, many algorithms inspired by natural behavior have emerged successfully aiming to find approximate solutions compatible with optimal ones, but with much higher performance in terms of computational time. Although they perform well, some of these newer algorithms have not yet been analyzed from their practical applicability in one or more medical databases. This paper presents a comparative study from a practical point of view of three of these new algorithms: Cuckoo Search (CS), KH (Krill Herd) and EHO (Elephant Herd Optimization). Our results suggest that these three algorithms are compatible in terms of performance in medical databases, but with EHO showing the best performance among all three.
{"title":"Comparison of Bio-Inspired Algorithms From The Point of View of Medical Image Segmentation","authors":"G. Wachs-Lopes, Fernanda S. Beltrame, R. M. Santos, P. Rodrigues","doi":"10.1109/IWOBI.2018.8464218","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464218","url":null,"abstract":"As new technological challenges depending on the computational performance of bio-inspired algorithms emerge, the demand for more efficient heuristic solutions grows up at same rate. Specifically, the medical field is one of the most challenging, due to the fact of the pre-processing steps, such as multilevel segmentation of color spaces, require greater precision. Thus, many algorithms inspired by natural behavior have emerged successfully aiming to find approximate solutions compatible with optimal ones, but with much higher performance in terms of computational time. Although they perform well, some of these newer algorithms have not yet been analyzed from their practical applicability in one or more medical databases. This paper presents a comparative study from a practical point of view of three of these new algorithms: Cuckoo Search (CS), KH (Krill Herd) and EHO (Elephant Herd Optimization). Our results suggest that these three algorithms are compatible in terms of performance in medical databases, but with EHO showing the best performance among all three.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127964264","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}
Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464183
Rebeca Campos-Sánchez, I. Sandoval-Carvajal
The human genome is crowded with transposable elements (TE), of which endogenous retroviruses (ERVs) are not the most studied from the perspective of expression, polymorphisms, and their influence on recent genome evolution. We studied expression data (RNA-Seq) from two human testis providing evidence that diverse families of ERVs are expressing in these tissues and that some ERV-derived transcripts overlap with genes or lncRNA annotations. Our pipeline can be applied to other human and primate samples to extend our knowledge of ERV's biology and their importance for germline genome evolution and disease.
{"title":"Detection of ERV-Derived Transcripts in Human Testis Using High Throughput Sequencing: Pipeline for Annotation and Genomic Localization","authors":"Rebeca Campos-Sánchez, I. Sandoval-Carvajal","doi":"10.1109/IWOBI.2018.8464183","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464183","url":null,"abstract":"The human genome is crowded with transposable elements (TE), of which endogenous retroviruses (ERVs) are not the most studied from the perspective of expression, polymorphisms, and their influence on recent genome evolution. We studied expression data (RNA-Seq) from two human testis providing evidence that diverse families of ERVs are expressing in these tissues and that some ERV-derived transcripts overlap with genes or lncRNA annotations. Our pipeline can be applied to other human and primate samples to extend our knowledge of ERV's biology and their importance for germline genome evolution and disease.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132459004","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}
Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464221
Daniel García-Vaglio, Federico Ruiz-Ugalde
Currently one of the most important challenges is to bring robots out of factory floors to work alongside humans. Because these environments are characterized by a very large variety of objects, a key factor is to provide them with better adaptive object manipulation skills. This means that robots are required to connect, in a meaningful way, a high level task to the robot body movements. Understanding the objects at a physical level can give a robot a connecting mechanism to the higher level system. A previous experiment showed that a robot can skillfully manipulate an object if it is provided with the right mathematical models and controllers [1]. We want to expand this experiment by creating a system that can generalize this type of object manipulation capabilities to many more objects and tasks. In this paper we propose an architecture that helps bridge this gap by using insights from primate cognition. This system enables robots to handle more objects, deal better with tools, and facilitate the process of reasoning about actions and their expected outcomes. We exercised our implementation with some simple testing object models, and were able to corroborate its proper behavior under the proposed circumstances.
{"title":"An Object Manipulation System Architecture for Humanoid Robots Based on Primate Cognition","authors":"Daniel García-Vaglio, Federico Ruiz-Ugalde","doi":"10.1109/IWOBI.2018.8464221","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464221","url":null,"abstract":"Currently one of the most important challenges is to bring robots out of factory floors to work alongside humans. Because these environments are characterized by a very large variety of objects, a key factor is to provide them with better adaptive object manipulation skills. This means that robots are required to connect, in a meaningful way, a high level task to the robot body movements. Understanding the objects at a physical level can give a robot a connecting mechanism to the higher level system. A previous experiment showed that a robot can skillfully manipulate an object if it is provided with the right mathematical models and controllers [1]. We want to expand this experiment by creating a system that can generalize this type of object manipulation capabilities to many more objects and tasks. In this paper we propose an architecture that helps bridge this gap by using insights from primate cognition. This system enables robots to handle more objects, deal better with tools, and facilitate the process of reasoning about actions and their expected outcomes. We exercised our implementation with some simple testing object models, and were able to corroborate its proper behavior under the proposed circumstances.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126493756","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}
Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464137
Calderon-Gomez Paola, Man-Sai Aeón-Chan, R. Mora-Rodríguez
The control of angiogenesis in cancer has been recognized as a promising therapeutic target for many diseases like cancer. Specifically, the Angiopoietin-2 - Vascular Endothelial Growth Factor system has demonstrated special relevance in the regulation of angiogenesis, highlighting the importance of the complex coordination among vascular signaling molecules [3] for the identification of targets for future anti-angiogenic therapy. Current approaches to regulate the angiogenesis process focus their efforts only on VEGF regulation but this has proven ineffective in many kinds of cancer, prompting the need for further understanding of how the vasculature can be effectively targeted in tumors [9]. Given the complex properties of gene expression in this process, a Systems Biology approach is required to identify putative candidates to robustly regulate genes involved in angiogenesis. We propose a model with candidate targets to downregulate the angiogenic genes expression. We identified a strong regulation of the AKT1-ANGPT2-KDR axis by miR200B and miR200C. Also, we identified a strong regulation of SRC by miR34a. These candidate miRNAs could therefore have a potential for the development of novel therapeutic strategies against angiogenesis in cancer.
{"title":"A Systems Biology Approach to Identify Candidate Targets to Downregulate Angiogenic Gene Expression in Cancer","authors":"Calderon-Gomez Paola, Man-Sai Aeón-Chan, R. Mora-Rodríguez","doi":"10.1109/IWOBI.2018.8464137","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464137","url":null,"abstract":"The control of angiogenesis in cancer has been recognized as a promising therapeutic target for many diseases like cancer. Specifically, the Angiopoietin-2 - Vascular Endothelial Growth Factor system has demonstrated special relevance in the regulation of angiogenesis, highlighting the importance of the complex coordination among vascular signaling molecules [3] for the identification of targets for future anti-angiogenic therapy. Current approaches to regulate the angiogenesis process focus their efforts only on VEGF regulation but this has proven ineffective in many kinds of cancer, prompting the need for further understanding of how the vasculature can be effectively targeted in tumors [9]. Given the complex properties of gene expression in this process, a Systems Biology approach is required to identify putative candidates to robustly regulate genes involved in angiogenesis. We propose a model with candidate targets to downregulate the angiogenic genes expression. We identified a strong regulation of the AKT1-ANGPT2-KDR axis by miR200B and miR200C. Also, we identified a strong regulation of SRC by miR34a. These candidate miRNAs could therefore have a potential for the development of novel therapeutic strategies against angiogenesis in cancer.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128172305","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}
Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464184
Á. García-Pedrero, A. García‐Cervigón, Cristina Caetano, S. C. Ramírez, J. M. Olano, C. Gonzalo-Martín, M. Lillo-Saavedra, M. García-Hidalgo
Xylem is a vascular tissue that conveys water and dissolved minerals from the roots to the rest of the plant and also provides physical support. The most important cells present in xylem are called vessels. These cells are arranged to form long pipes that carry water through the tree. The identification, counting and subsequent characterization of xylem vessels is essential for monitoring tree health and its relationship with climatic conditions. Although automatic and semi-automatic image processing tools are available to analyze the structure of xylem at the cellular level, they usually require the supervision of an expert to obtain optimal segmentation, making it a highly time-consuming process. To overcome this limitation, a Convolutional Neural Network model was used to process digital images of 23 branch sections in order to segment the xylem vessels. The obtained results were compared with other two classical methods, Otsu's thresholding method, and an active contour method known as Chan-Vese segmentation algorithm. The obtained results show the potential of convolutional neural networks to overcome aspects such as non-homogeneous illumination of images, where conventional methods tend to obtain unsatisfactory results.
{"title":"Xylem Vessels Segmentation Through a Deep Learning Approach: a First Look","authors":"Á. García-Pedrero, A. García‐Cervigón, Cristina Caetano, S. C. Ramírez, J. M. Olano, C. Gonzalo-Martín, M. Lillo-Saavedra, M. García-Hidalgo","doi":"10.1109/IWOBI.2018.8464184","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464184","url":null,"abstract":"Xylem is a vascular tissue that conveys water and dissolved minerals from the roots to the rest of the plant and also provides physical support. The most important cells present in xylem are called vessels. These cells are arranged to form long pipes that carry water through the tree. The identification, counting and subsequent characterization of xylem vessels is essential for monitoring tree health and its relationship with climatic conditions. Although automatic and semi-automatic image processing tools are available to analyze the structure of xylem at the cellular level, they usually require the supervision of an expert to obtain optimal segmentation, making it a highly time-consuming process. To overcome this limitation, a Convolutional Neural Network model was used to process digital images of 23 branch sections in order to segment the xylem vessels. The obtained results were compared with other two classical methods, Otsu's thresholding method, and an active contour method known as Chan-Vese segmentation algorithm. The obtained results show the potential of convolutional neural networks to overcome aspects such as non-homogeneous illumination of images, where conventional methods tend to obtain unsatisfactory results.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124282242","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}
Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464197
L. D. Murillo-Soto, Geovanni Figueroa-Mata, Carlos Meza
One of the main concern of the maintenance operation in solar plants is the early identification of faults in solar panels. Several faults in solar panels reflects on the variation of its internal resistance. This work presents and validates a differential evolution algorithm that is capable of identifying the changes on the internal resistance of photo-voltaic (PV) modules under dark conditions. Such algorithm enables the automated test of PV modules during the night, when the identification operations do not affect the PV installation energy generation.
{"title":"Identification of the Internal Resistance in Solar Modules Under Dark Conditions Using Differential Evolution Algorithm","authors":"L. D. Murillo-Soto, Geovanni Figueroa-Mata, Carlos Meza","doi":"10.1109/IWOBI.2018.8464197","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464197","url":null,"abstract":"One of the main concern of the maintenance operation in solar plants is the early identification of faults in solar panels. Several faults in solar panels reflects on the variation of its internal resistance. This work presents and validates a differential evolution algorithm that is capable of identifying the changes on the internal resistance of photo-voltaic (PV) modules under dark conditions. Such algorithm enables the automated test of PV modules during the night, when the identification operations do not affect the PV installation energy generation.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123522939","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}
Pub Date : 2018-07-01DOI: 10.1109/IWOBI.2018.8464198
M. Castresana, Francisco Siles
Nowadays , motion capture technology is used in productions of all levels in 3D Animation. The concept on which this technology is based on, consists of the elaboration of 3D models from numerical data taken by a set of sensors (for example infrared cameras) interpreted by a software. The problem with this technology is that the processing of data generated by these sensors is not always accurate, causing loss of positional data which results in errors called glitches, that produce corrupted 3D models. In this work, a goniometry-based algorithm to detect, locate and correct the glitches generated from optical motion capture data is presented. Based on the classification of angular measures of the articular physiology in humans, a pattern recognition approach was used to construct the algorithm. The proposed algorithm produces average F1-scores of 0.956 using synthetical data, and produces natural results in most of the cases for real data.
{"title":"Goniometry-based Glitch-Correction Algorithm for Optical Motion Capture Data","authors":"M. Castresana, Francisco Siles","doi":"10.1109/IWOBI.2018.8464198","DOIUrl":"https://doi.org/10.1109/IWOBI.2018.8464198","url":null,"abstract":"Nowadays , motion capture technology is used in productions of all levels in 3D Animation. The concept on which this technology is based on, consists of the elaboration of 3D models from numerical data taken by a set of sensors (for example infrared cameras) interpreted by a software. The problem with this technology is that the processing of data generated by these sensors is not always accurate, causing loss of positional data which results in errors called glitches, that produce corrupted 3D models. In this work, a goniometry-based algorithm to detect, locate and correct the glitches generated from optical motion capture data is presented. Based on the classification of angular measures of the articular physiology in humans, a pattern recognition approach was used to construct the algorithm. The proposed algorithm produces average F1-scores of 0.956 using synthetical data, and produces natural results in most of the cases for real data.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124490060","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}
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