We present an approach for merging into a single super-image a set of uncalibrated images of a general 3D scene taken from multiple viewpoints. To this aim, the content of either image is augmented with visual information taken from the others, while maintaining projective coherence. The approach extends the usual mosaicing techniques to image collections with3D parallax, and operates like a virtual sensor provided with an enlarged field of view and the capability of seeing through visual occlusions in an "X-ray" fashion. Fundamental matrices are used to transfer visual information through the vertexes of an image graph. A dense stereo paradigm is employed to achieve photorealism by partitioning image pairs into corresponding regions. Results in oriented projective geometry are then exploited to both detect and handle occlusions by assessing the visibility properties of each transferred point.
{"title":"Augmented Vision: Seeing beyond Field of View and Occlusions via Uncalibrated Visual Transfer from Multiple Viewpoints","authors":"Antonella Nardi, Dario Comanducci, C. Colombo","doi":"10.1109/IMVIP.2011.16","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.16","url":null,"abstract":"We present an approach for merging into a single super-image a set of uncalibrated images of a general 3D scene taken from multiple viewpoints. To this aim, the content of either image is augmented with visual information taken from the others, while maintaining projective coherence. The approach extends the usual mosaicing techniques to image collections with3D parallax, and operates like a virtual sensor provided with an enlarged field of view and the capability of seeing through visual occlusions in an \"X-ray\" fashion. Fundamental matrices are used to transfer visual information through the vertexes of an image graph. A dense stereo paradigm is employed to achieve photorealism by partitioning image pairs into corresponding regions. Results in oriented projective geometry are then exploited to both detect and handle occlusions by assessing the visibility properties of each transferred point.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114370744","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}
It is not acceptable to use loss less techniques when compressing medical image data, and as a result, it is difficult to achieve high compression ratios. We have developed a novel segmentation based compression scheme to overcome this problem and our experimental results indicate that this scheme is capable of achieving a high level of compression without sacrificing the quality of the patient data.
{"title":"A Segmentation Based Lossless Compression Scheme for Volumetric Medical Image Data","authors":"Qiusha Min, R. Sadleir","doi":"10.1109/IMVIP.2011.26","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.26","url":null,"abstract":"It is not acceptable to use loss less techniques when compressing medical image data, and as a result, it is difficult to achieve high compression ratios. We have developed a novel segmentation based compression scheme to overcome this problem and our experimental results indicate that this scheme is capable of achieving a high level of compression without sacrificing the quality of the patient data.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131466228","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}
In this paper, we present an effective method for integrating 3D augmented reality graphics into single images taken in urban environments. Building facades usually contain a large number of parallel lines aligned along several principal directions. We make use of the images of these 3D parallel lines and their corresponding vanishing points to recover a number of 3D planes from single 2D images of urban environments and then use them to represent the spatial layout of a scene. 3D objects are then aligned with respect to these recovered planes to achieve realistic augmented reality effects. In experiments we applied the proposed method to implement augmented reality in images from a benchmark image dataset of urban environments.
{"title":"Single Image Augmented Reality Using Planar Structures in Urban Environments","authors":"Eric McClean, Yanpeng Cao, J. McDonald","doi":"10.1109/IMVIP.2011.10","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.10","url":null,"abstract":"In this paper, we present an effective method for integrating 3D augmented reality graphics into single images taken in urban environments. Building facades usually contain a large number of parallel lines aligned along several principal directions. We make use of the images of these 3D parallel lines and their corresponding vanishing points to recover a number of 3D planes from single 2D images of urban environments and then use them to represent the spatial layout of a scene. 3D objects are then aligned with respect to these recovered planes to achieve realistic augmented reality effects. In experiments we applied the proposed method to implement augmented reality in images from a benchmark image dataset of urban environments.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129449255","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}
Michael Brogan, S. Haughey, S. Murray, C. Deegan, S. McLoughlin, C. Fitzgerald
A Mobile Mapping System (MMS) has been designed by the Intelligent Transportation Systems (ITS) research group at the Institute of Technology Blanchard town (ITB). This system detects, geo-references and evaluates road delineation data for the purposes of road marking maintenance. It consists of a monochrome stereo camera system integrated with a tightly-coupled Global Positioning System/Inertial Navigation System (GPS/INS), allowing stereo images to be acquired with navigational data, allowing for geo-referencing of detected road markings. An essential step in this process is the calibration of the cameras, and relates the pose of the two cameras to each other and a world co-ordinate system. Road markings must be evaluated from a 35 m range so the cameras are required to have a wide field of view. Traditional calibration methods supposedly require a calibration object that would fill most of the calibration images. This large field of view would require a calibration object of substantial size that would be impractical for the purposes of this portable system. This paper gives an overview of the MMS, explores the theory of camera calibration and then details two camera calibration techniques (using a three-dimensional calibration object and two-dimensional object). The accuracy of these methods is then evaluated using a ground truth experiment.
{"title":"Comparison of Camera Calibration Techniques for a Portable Mobile Mapping System","authors":"Michael Brogan, S. Haughey, S. Murray, C. Deegan, S. McLoughlin, C. Fitzgerald","doi":"10.1109/IMVIP.2011.18","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.18","url":null,"abstract":"A Mobile Mapping System (MMS) has been designed by the Intelligent Transportation Systems (ITS) research group at the Institute of Technology Blanchard town (ITB). This system detects, geo-references and evaluates road delineation data for the purposes of road marking maintenance. It consists of a monochrome stereo camera system integrated with a tightly-coupled Global Positioning System/Inertial Navigation System (GPS/INS), allowing stereo images to be acquired with navigational data, allowing for geo-referencing of detected road markings. An essential step in this process is the calibration of the cameras, and relates the pose of the two cameras to each other and a world co-ordinate system. Road markings must be evaluated from a 35 m range so the cameras are required to have a wide field of view. Traditional calibration methods supposedly require a calibration object that would fill most of the calibration images. This large field of view would require a calibration object of substantial size that would be impractical for the purposes of this portable system. This paper gives an overview of the MMS, explores the theory of camera calibration and then details two camera calibration techniques (using a three-dimensional calibration object and two-dimensional object). The accuracy of these methods is then evaluated using a ground truth experiment.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132194887","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}
A strategy is proposed that enhances the local feature matching capabilities of the SURF descriptor by utilising colour histograms. The results compare variations of the RGB, HSV and Opponent colour spaces on a dataset of image pairs that undergo illumination, viewpoint and translational changes. This study finds the most appropriate colour space that enhances the distinctiveness of a descriptor when applied to the matching of corresponding features in arbitrary image sets.
{"title":"Enhancing SURF Feature Matching Using Colour Histograms","authors":"T. M. Barroso, P. Whelan","doi":"10.1109/IMVIP.2011.31","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.31","url":null,"abstract":"A strategy is proposed that enhances the local feature matching capabilities of the SURF descriptor by utilising colour histograms. The results compare variations of the RGB, HSV and Opponent colour spaces on a dataset of image pairs that undergo illumination, viewpoint and translational changes. This study finds the most appropriate colour space that enhances the distinctiveness of a descriptor when applied to the matching of corresponding features in arbitrary image sets.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123878281","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}
Structural information available from the granulometry of an image has been used widely in image texture analysis and classification. In this paper we present a method for classifying texture images which follow an intrinsic ordering of textures, using polynomial regression to express granulometric moments as a function of class label. Separate models are built for each individual moment and combined for back-prediction of the class label of a new image. The methodology was developed on synthetic images of evolving textures and tested using real images of 8 different grades of cut-tear-curl black tea leaves. For comparison, grey level co-occurrence (GLCM) based features were also computed, and both feature types were used in a range of classifiers including the regression approach. Experimental results demonstrate the superiority of the granulometric moments over GLCM-based features for classifying these tea images.
{"title":"Classification of Ordered Texture Images Using Regression Modelling and Granulometric Features","authors":"M. Khatun, A. Gray, S. Marshall","doi":"10.1109/IMVIP.2011.20","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.20","url":null,"abstract":"Structural information available from the granulometry of an image has been used widely in image texture analysis and classification. In this paper we present a method for classifying texture images which follow an intrinsic ordering of textures, using polynomial regression to express granulometric moments as a function of class label. Separate models are built for each individual moment and combined for back-prediction of the class label of a new image. The methodology was developed on synthetic images of evolving textures and tested using real images of 8 different grades of cut-tear-curl black tea leaves. For comparison, grey level co-occurrence (GLCM) based features were also computed, and both feature types were used in a range of classifiers including the regression approach. Experimental results demonstrate the superiority of the granulometric moments over GLCM-based features for classifying these tea images.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127132054","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}
This paper presents an approach of visual SLAM using line segments as primitives. We choose Plucker lines to represent spatial lines and derive a novel fast line projection function based on the relationship between Pl̈ucker line and Plucker matrix. During normal SLAM procedure, the Near by Line Tracking (NLT) method is adopted to track lines and an Extended Kalman Filter (EKF) is used to predict and update the state of the camera and line landmarks. After each update step, a robust spatial line reconstruction algorithm is used to find new line landmarks and to add them into the map. The SLAM procedure is under supervision and when failure is detected, a recovery method based on the angle histogram of key frames is adopted to relocalize the camera and re-start the SLAM procedure. We demonstrate that our monocular SLAM system is robust to illumination change, partial occlusion and fast camera motion.
{"title":"Hand-Held Monocular SLAM Based on Line Segments","authors":"Lilian Zhang, R. Koch","doi":"10.1109/IMVIP.2011.11","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.11","url":null,"abstract":"This paper presents an approach of visual SLAM using line segments as primitives. We choose Plucker lines to represent spatial lines and derive a novel fast line projection function based on the relationship between Pl̈ucker line and Plucker matrix. During normal SLAM procedure, the Near by Line Tracking (NLT) method is adopted to track lines and an Extended Kalman Filter (EKF) is used to predict and update the state of the camera and line landmarks. After each update step, a robust spatial line reconstruction algorithm is used to find new line landmarks and to add them into the map. The SLAM procedure is under supervision and when failure is detected, a recovery method based on the angle histogram of key frames is adopted to relocalize the camera and re-start the SLAM procedure. We demonstrate that our monocular SLAM system is robust to illumination change, partial occlusion and fast camera motion.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127762374","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}
Henrike Stephani, B. Heise, S. Katletz, K. Wiesauer, D. Molter, J. Jonuscheit, R. Beigang
Terahertz time-domain spectroscopic imaging (THz-TDS imaging) producesimages with hundreds of channels. Automatic as well as manual imageanalysis is therefore difficult. We propose to use a feature set thatreduces the number of channels down to 21 and still preserves all importantinformation. Both spectral and time-domain features areincluded in this set, and thereby information aboutdifferent content is gained. We show the practicalapplicability of this approach, by using it on images from different areas of interest. Wefurthermore illustrate its advantages to the classical approach byperforming a clustering-based image segmentation on the full spectraldata and the proposed feature set. Using this reduced but representative information improves thesegmentation quality and makes THz-TDS imageprocessing and segmentation feasible and less prone to the``curse of dimensionality''.
{"title":"A Feature Set for Enhanced Automatic Segmentation of Hyperspectral Terahertz Images","authors":"Henrike Stephani, B. Heise, S. Katletz, K. Wiesauer, D. Molter, J. Jonuscheit, R. Beigang","doi":"10.1109/IMVIP.2011.34","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.34","url":null,"abstract":"Terahertz time-domain spectroscopic imaging (THz-TDS imaging) producesimages with hundreds of channels. Automatic as well as manual imageanalysis is therefore difficult. We propose to use a feature set thatreduces the number of channels down to 21 and still preserves all importantinformation. Both spectral and time-domain features areincluded in this set, and thereby information aboutdifferent content is gained. We show the practicalapplicability of this approach, by using it on images from different areas of interest. Wefurthermore illustrate its advantages to the classical approach byperforming a clustering-based image segmentation on the full spectraldata and the proposed feature set. Using this reduced but representative information improves thesegmentation quality and makes THz-TDS imageprocessing and segmentation feasible and less prone to the``curse of dimensionality''.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114794697","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}
Y. Pratheepan, J. Condell, K. Curran, P. Kevitt, A. Cheddad
The Internet is a widely open source to everyone to access Web pages. Using a web browser anyone can access websites. Because of this facility people can easily download images from websites without the owner's knowledge and use them in their own documents. Also image content may be modified for illegal purposes. Therefore a system is needed to authenticate images over the Web. Web image authentication is a challenging task that requires web crawlers to track and download images for authentication. Most of the known web image tracking engines such as Tin Eye and PicScout retrieve images according to the image infringement of the original image. However, these systems do not have the facility to authenticate the retrieved image, i.e. whether the retrieved image is similar to the original image or any image content alteration has occurred in the retrieved image and who is the copyrighted owner of the retrieved image. In order to solve the above mentioned drawbacks this paper presents a framework to protect image content, track it over the internet and authenticate the content. The proposed framework is based on self-embedding (i.e. where secret data and a binary version of the image are encrypted and embedded into the image), tracking (i.e. where a web crawler traverses over the internet to download images) and self-authentication (i.e. where the binary version of the hidden data is extracted to authenticate the image). Also another advantage of the proposed system is that it does not need the original image for the authentication process.
{"title":"Embed, Track and Authenticate Images Online with SDW-WebCrawler","authors":"Y. Pratheepan, J. Condell, K. Curran, P. Kevitt, A. Cheddad","doi":"10.1109/IMVIP.2011.22","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.22","url":null,"abstract":"The Internet is a widely open source to everyone to access Web pages. Using a web browser anyone can access websites. Because of this facility people can easily download images from websites without the owner's knowledge and use them in their own documents. Also image content may be modified for illegal purposes. Therefore a system is needed to authenticate images over the Web. Web image authentication is a challenging task that requires web crawlers to track and download images for authentication. Most of the known web image tracking engines such as Tin Eye and PicScout retrieve images according to the image infringement of the original image. However, these systems do not have the facility to authenticate the retrieved image, i.e. whether the retrieved image is similar to the original image or any image content alteration has occurred in the retrieved image and who is the copyrighted owner of the retrieved image. In order to solve the above mentioned drawbacks this paper presents a framework to protect image content, track it over the internet and authenticate the content. The proposed framework is based on self-embedding (i.e. where secret data and a binary version of the image are encrypted and embedded into the image), tracking (i.e. where a web crawler traverses over the internet to download images) and self-authentication (i.e. where the binary version of the hidden data is extracted to authenticate the image). Also another advantage of the proposed system is that it does not need the original image for the authentication process.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128065360","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}
Anil Kumar, P. Chavan, Sharatchandra V K, S. David, Philip Kelly, Noel E O 'connor
In this work, we develop image processing and computer vision techniques for visually tracking a tennis ball, in 3D, on a court instrumented with multiple low-cost IP cameras. The technique first obtains 2D ball tracking data from each camera view using 2D object tracking methods. Next, an automatic feature-based video synchronization method is applied. This technique uses the extracted 2D ball information from two or more camera views, plus camera calibration information. In order to find 3D trajectory, the temporal 3D locations of the ball is estimated using triangulation of correspondent 2D locations obtained from automatically synchronized videos. Furthermore, in order to improve the continuity of the tracked 3D ball during times when no two cameras have overlapping views of the ball location, we incorporate a physics-based trajectory model into the system. The resultant 3D ball tracks are then visualized in a virtual 3D graphical environment. Finally, we quantify the accuracy of our system in terms of reprojection error.
{"title":"3D Estimation and Visualization of Motion in a Multicamera Network for Sports","authors":"Anil Kumar, P. Chavan, Sharatchandra V K, S. David, Philip Kelly, Noel E O 'connor","doi":"10.1109/IMVIP.2011.12","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.12","url":null,"abstract":"In this work, we develop image processing and computer vision techniques for visually tracking a tennis ball, in 3D, on a court instrumented with multiple low-cost IP cameras. The technique first obtains 2D ball tracking data from each camera view using 2D object tracking methods. Next, an automatic feature-based video synchronization method is applied. This technique uses the extracted 2D ball information from two or more camera views, plus camera calibration information. In order to find 3D trajectory, the temporal 3D locations of the ball is estimated using triangulation of correspondent 2D locations obtained from automatically synchronized videos. Furthermore, in order to improve the continuity of the tracked 3D ball during times when no two cameras have overlapping views of the ball location, we incorporate a physics-based trajectory model into the system. The resultant 3D ball tracks are then visualized in a virtual 3D graphical environment. Finally, we quantify the accuracy of our system in terms of reprojection error.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122483755","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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