Previously a particle filter has been proposed to detect colour objects in video [1]. In this work, the particle filter is adapted to track people in surveillance video. Detection is based on automated background modelling rather than a manually-generated object colour model. A labelling method is proposed that tracks objects through the scene rather than detecting them. A methodical comparison between the new method and two other multi-object trackers is presented on the PETS 2004 benchmark data set. The particle filter gives significantly fewer false alarms due to explicit modelling of the object birth and death processes, while maintaining a good detection rate.
{"title":"Evaluation of a Particle Filter to Track People for Visual Surveillance","authors":"J. Sherrah, B. Ristic, N. Redding","doi":"10.1109/DICTA.2009.24","DOIUrl":"https://doi.org/10.1109/DICTA.2009.24","url":null,"abstract":"Previously a particle filter has been proposed to detect colour objects in video [1]. In this work, the particle filter is adapted to track people in surveillance video. Detection is based on automated background modelling rather than a manually-generated object colour model. A labelling method is proposed that tracks objects through the scene rather than detecting them. A methodical comparison between the new method and two other multi-object trackers is presented on the PETS 2004 benchmark data set. The particle filter gives significantly fewer false alarms due to explicit modelling of the object birth and death processes, while maintaining a good detection rate.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124724348","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. Obaid, R. Mukundan, Hartmut Goecke, M. Billinghurst, H. Seichter
In this paper, we propose a novel approach for recognizing facial expressions based on using an Active Appearance Model facial feature tracking system with the quadratic deformation model representations of facial expressions. Thirty seven Facial Feature points are tracked based on the MPEG-4 Facial Animation Parameters layout. The proposed approach relies on the Euclidean distance measures between the tracked feature points and the reference deformed facial feature points of the six main expressions (smile, sad, fear, disgust, surprise, and anger). An evaluation of 30 model subjects, selected randomly from the Cohn-Kanade Database, was carried out. Results show that the main six facial expressions can successfully be recognized with an overall recognition accuracy of 89%. The proposed approach yields to promising recognition rates and can be used in real time applications.
{"title":"A Quadratic Deformation Model for Facial Expression Recognition","authors":"M. Obaid, R. Mukundan, Hartmut Goecke, M. Billinghurst, H. Seichter","doi":"10.1109/DICTA.2009.51","DOIUrl":"https://doi.org/10.1109/DICTA.2009.51","url":null,"abstract":"In this paper, we propose a novel approach for recognizing facial expressions based on using an Active Appearance Model facial feature tracking system with the quadratic deformation model representations of facial expressions. Thirty seven Facial Feature points are tracked based on the MPEG-4 Facial Animation Parameters layout. The proposed approach relies on the Euclidean distance measures between the tracked feature points and the reference deformed facial feature points of the six main expressions (smile, sad, fear, disgust, surprise, and anger). An evaluation of 30 model subjects, selected randomly from the Cohn-Kanade Database, was carried out. Results show that the main six facial expressions can successfully be recognized with an overall recognition accuracy of 89%. The proposed approach yields to promising recognition rates and can be used in real time applications.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128594840","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}
We are interested in the problem of automatically tracking football players, subject to the constraint that only one vantage point is available. Tracking algorithms benefit from seeing the entire playing field, as one does not have to worry about objects entering and leaving the field of view. However, the image of the entire field must be of sufficient resolution to allow each of the players to be identified automatically. To achieve this desired video data, several high definition video cameras are used to record a football match from a single vantage point. The cameras are oriented to cover the entire playing field, and their images combined to create a single high-resolution video feed. The user is able to pan and zoom in real-time within the unified video stream while it is playing. The system is achieved by distributing tasks across a network of computers and only processing data that will be visible to the user.
{"title":"Portable Multi-megapixel Camera with Real-Time Recording and Playback","authors":"Peter Carr, R. Hartley","doi":"10.1109/DICTA.2009.62","DOIUrl":"https://doi.org/10.1109/DICTA.2009.62","url":null,"abstract":"We are interested in the problem of automatically tracking football players, subject to the constraint that only one vantage point is available. Tracking algorithms benefit from seeing the entire playing field, as one does not have to worry about objects entering and leaving the field of view. However, the image of the entire field must be of sufficient resolution to allow each of the players to be identified automatically. To achieve this desired video data, several high definition video cameras are used to record a football match from a single vantage point. The cameras are oriented to cover the entire playing field, and their images combined to create a single high-resolution video feed. The user is able to pan and zoom in real-time within the unified video stream while it is playing. The system is achieved by distributing tasks across a network of computers and only processing data that will be visible to the user.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116637626","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 novel image compression scheme that takes advantages of side-match vector quantization (SMVQ) and search-order-coding (SOC) algorithm is proposed in this article. In the proposed scheme, the image to be compressed is firstly encoded into an index table by applying the traditional SMVQ compression technique. Then, the index table of image is further compressed based on the ordinary SOC algorithm. To improve the compression efficiency of the proposed scheme, a modified search-order-coding algorithm, called left-upper-coding (LUC), is designed. The performance comparison between the two SOC algorithms has been conducted in our computer simulation. Experimental results show that the SOC algorithm functions very well with SMVQ, and the LUC algorithm is more feasible for compressing the SMVQ indexes of image when the computational efficiency is concerned.
{"title":"Image Compression Based on Side-Match VQ and SOC","authors":"S. Shie, Long-Tai Chen","doi":"10.1109/DICTA.2009.68","DOIUrl":"https://doi.org/10.1109/DICTA.2009.68","url":null,"abstract":"A novel image compression scheme that takes advantages of side-match vector quantization (SMVQ) and search-order-coding (SOC) algorithm is proposed in this article. In the proposed scheme, the image to be compressed is firstly encoded into an index table by applying the traditional SMVQ compression technique. Then, the index table of image is further compressed based on the ordinary SOC algorithm. To improve the compression efficiency of the proposed scheme, a modified search-order-coding algorithm, called left-upper-coding (LUC), is designed. The performance comparison between the two SOC algorithms has been conducted in our computer simulation. Experimental results show that the SOC algorithm functions very well with SMVQ, and the LUC algorithm is more feasible for compressing the SMVQ indexes of image when the computational efficiency is concerned.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123019842","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}
Weihong Wang, Chunhua Shen, Jian Zhang, S. Paisitkriangkrai
We present a two-layer night time vehicle detector in this work. At the first layer, vehicle headlight detection is applied to find areas (bounding boxes) where the possible pairs of headlights locate in the image, the Haar feature based AdaBoost framework is then applied to detect the vehicle front. This approach has achieved a very promising performance for vehicle detection at night time. Our results show that the proposed algorithm can obtain a detection rate of over 90% at a very low false positive rate (1.5%). Without any code optimization, it also performs at a faster speed compared to the standard Haar feature based AdaBoost approach.
{"title":"A Two-Layer Night-Time Vehicle Detector","authors":"Weihong Wang, Chunhua Shen, Jian Zhang, S. Paisitkriangkrai","doi":"10.1109/DICTA.2009.33","DOIUrl":"https://doi.org/10.1109/DICTA.2009.33","url":null,"abstract":"We present a two-layer night time vehicle detector in this work. At the first layer, vehicle headlight detection is applied to find areas (bounding boxes) where the possible pairs of headlights locate in the image, the Haar feature based AdaBoost framework is then applied to detect the vehicle front. This approach has achieved a very promising performance for vehicle detection at night time. Our results show that the proposed algorithm can obtain a detection rate of over 90% at a very low false positive rate (1.5%). Without any code optimization, it also performs at a faster speed compared to the standard Haar feature based AdaBoost approach.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134496943","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 method based on sublevel sets is presented for refining segmentation of screening mammograms. Initial segmentation is provided by an adaptive pyramid (AP) scheme which is viewed as seeding of the final segmentation by sublevel sets. Performance is tested with and without prior anisotropic smoothing and is compared to refinement based on component merging. The combination of anisotropic smoothing, AP segmentation and sublevel refinement is found to outperform other combinations.
{"title":"Automatic Mass Segmentation Based on Adaptive Pyramid and Sublevel Set Analysis","authors":"Fei Ma, M. Bajger, M. Bottema","doi":"10.1109/DICTA.2009.47","DOIUrl":"https://doi.org/10.1109/DICTA.2009.47","url":null,"abstract":"A method based on sublevel sets is presented for refining segmentation of screening mammograms. Initial segmentation is provided by an adaptive pyramid (AP) scheme which is viewed as seeding of the final segmentation by sublevel sets. Performance is tested with and without prior anisotropic smoothing and is compared to refinement based on component merging. The combination of anisotropic smoothing, AP segmentation and sublevel refinement is found to outperform other combinations.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"99 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134287427","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}
F. She, R. H. Chen, W. Gao, P. Hodgson, L. Kong, H. Hong
In this study, we focused on developing a novel 3D Thinning algorithm to extract one-voxel wide skeleton from various 3D objects aiming at preserving the topological information. The 3D Thinning algorithm was testified on computer-generated and real 3D reconstructed image sets acquired from TEMT and compared with other existing 3D Thinning algorithms. It is found that the algorithm has conserved medial axes and simultaneously topologies very well, demonstrating many advantages over the existing technologies. They are versatile, rigorous, efficient and rotation invariant.
{"title":"Improved 3D Thinning Algorithms for Skeleton Extraction","authors":"F. She, R. H. Chen, W. Gao, P. Hodgson, L. Kong, H. Hong","doi":"10.1109/DICTA.2009.13","DOIUrl":"https://doi.org/10.1109/DICTA.2009.13","url":null,"abstract":"In this study, we focused on developing a novel 3D Thinning algorithm to extract one-voxel wide skeleton from various 3D objects aiming at preserving the topological information. The 3D Thinning algorithm was testified on computer-generated and real 3D reconstructed image sets acquired from TEMT and compared with other existing 3D Thinning algorithms. It is found that the algorithm has conserved medial axes and simultaneously topologies very well, demonstrating many advantages over the existing technologies. They are versatile, rigorous, efficient and rotation invariant.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130583105","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 shows that most surveillance cameras fall well short of providing sufficient image quality, in both spatial resolution and colour reproduction, for the reliable identification of faces. In addition, the low resolution of surveillance images means that when compression is applied the MPEG/JPEG DCT block size can be such that the spatial frequencies most important for face recognition are corrupted. Making things even worse, the compression process heavily quantizes colour information disrupting the use of pigmentation information to recognize faces. Indeed, the term 'security camera' is probably misplaced. Many surveillance cameras are legally blind, or nearly so.
{"title":"Video Surveillance: Legally Blind?","authors":"P. Kovesi","doi":"10.1109/DICTA.2009.41","DOIUrl":"https://doi.org/10.1109/DICTA.2009.41","url":null,"abstract":"This paper shows that most surveillance cameras fall well short of providing sufficient image quality, in both spatial resolution and colour reproduction, for the reliable identification of faces. In addition, the low resolution of surveillance images means that when compression is applied the MPEG/JPEG DCT block size can be such that the spatial frequencies most important for face recognition are corrupted. Making things even worse, the compression process heavily quantizes colour information disrupting the use of pigmentation information to recognize faces. Indeed, the term 'security camera' is probably misplaced. Many surveillance cameras are legally blind, or nearly so.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"44 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114120510","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 addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the ‘wet’ areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.
{"title":"Mixed Pixel Analysis for Flood Mapping Using Extended Support Vector Machine","authors":"C. Dey, X. Jia, D. Fraser, L. Wang","doi":"10.1109/DICTA.2009.55","DOIUrl":"https://doi.org/10.1109/DICTA.2009.55","url":null,"abstract":"This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the ‘wet’ areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114194679","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}
Len Hamey, R. Connally, Simon Wong Too Yen, Thomas S. Lawson, J. Piper, J. Iredell
Fluorescence microscopy is a powerful tool for the rapid identification of target organisms. However, natural autofluorescence often interferes with identification. Time-gated luminescence microscopy (TGLM) uses luminescent labels with long persistence in conjunction with digital imaging to regain discriminative power. Following the excitation pulse, short-lived autofluorescence decays rapidly whereas the long-lived emission from lanthanide doped polymer beads persists for hundreds of microseconds. After a short resolving period, a gated high gain camera captures the persistent emission in the absence of short-lived fluorescence. We report on the development of a TGLM software system for automated scanning of microscope slides, and show its use to resolve luminescent microspheres within a matrix of autofluorescent algae.
{"title":"Luminescent Microspheres Resolved from Strong Background on an Automated Time-Gated Luminescence Microscopy Workstation","authors":"Len Hamey, R. Connally, Simon Wong Too Yen, Thomas S. Lawson, J. Piper, J. Iredell","doi":"10.1109/DICTA.2009.44","DOIUrl":"https://doi.org/10.1109/DICTA.2009.44","url":null,"abstract":"Fluorescence microscopy is a powerful tool for the rapid identification of target organisms. However, natural autofluorescence often interferes with identification. Time-gated luminescence microscopy (TGLM) uses luminescent labels with long persistence in conjunction with digital imaging to regain discriminative power. Following the excitation pulse, short-lived autofluorescence decays rapidly whereas the long-lived emission from lanthanide doped polymer beads persists for hundreds of microseconds. After a short resolving period, a gated high gain camera captures the persistent emission in the absence of short-lived fluorescence. We report on the development of a TGLM software system for automated scanning of microscope slides, and show its use to resolve luminescent microspheres within a matrix of autofluorescent algae.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122375155","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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