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| Author | Mikhail Mozerov; Ariel Amato; Xavier Roca | ||||
| Title | Occlusion Handling in Trinocular Stereo using Composite Disparity Space Image | Type | Conference Article | ||
| Year | 2009 | Publication | 19th International Conference on Computer Graphics and Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 69–73 | ||
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| Abstract | In this paper we propose a method that smartly improves occlusion handling in stereo matching using trinocular stereo. The main idea is based on the assumption that any occluded region in a matched stereo pair (middle-left images) in general is not occluded in the opposite matched pair (middle-right images). Then two disparity space images (DSI) can be merged in one composite DSI. The proposed integration differs from the known approach that uses a cumulative cost. A dense disparity map is obtained with a global optimization algorithm using the proposed composite DSI. The experimental results are evaluated on the Middlebury data set, showing high performance of the proposed algorithm especially in the occluded regions. One of the top positions in the rank of the Middlebury website confirms the performance of our method to be competitive with the best stereo matching. | ||||
| Address | Moscow (Russia) | ||||
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| ISSN | ISBN | 978-5-317-02975-3 | Medium | ||
| Area | Expedition | Conference | GRAPHICON | ||
| Notes | ISE | Approved | no | ||
Call Number  |
ISE @ ise @ MAR2009b | Serial | 1207 | ||
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| Author | Mikhail Mozerov; Ariel Amato; Xavier Roca; Jordi Gonzalez | ||||
| Title | Solving the Multi Object Occlusion Problem in a Multiple Camera Tracking System | Type | Journal | ||
| Year | 2009 | Publication | Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 19 | Issue | 1 | Pages | 165-171 |
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| Abstract | An efficient method to overcome adverse effects of occlusion upon object tracking is presented. The method is based on matching paths of objects in time and solves a complex occlusion-caused problem of merging separate segments of the same path. | ||||
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| ISSN | 1054-6618 | ISBN | Medium | ||
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| Notes | ISE | Approved | no | ||
| Call Number |
ISE @ ise @ MAR2009a | Serial | 1160 | ||
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| Author | Mikhail Mozerov; Ariel Amato; Xavier Roca; Jordi Gonzalez | ||||
| Title | Trajectory Occlusion Handling with Multiple View Distance Minimisation Clustering | Type | Journal | ||
| Year | 2008 | Publication | Optical Engineering, vol. 47(04)04702, DOI:10.11781.2909665 | Abbreviated Journal | |
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| Notes | ISE | Approved | no | ||
| Call Number |
ISE @ ise @ MAR2008c | Serial | 970 | ||
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| Author | Yuhua Luo; Francisco Jose Perales; Juan J. Villanueva | ||||
| Title | An automatic Rotoscopy System for Human Motion Based on a Biomedical Graphical Model. | Type | Journal Article | ||
| Year | 1992 | Publication | Computer & Graphics | Abbreviated Journal | |
| Volume | 16 | Issue | 4 | Pages | 355-362 |
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| Notes | Approved | no | |||
| Call Number |
ISE @ ise @ LPV1992 | Serial | 249 | ||
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| Author | V. Kober; Mikhail Mozerov; Josue Albarez; I.A. Ovseyevich | ||||
| Title | Algorithms for Impulse Noise Renoval from Corrupted Color Images | Type | Journal | ||
| Year | 2007 | Publication | Abbreviated Journal | ||
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| Notes | ISE | Approved | no | ||
| Call Number |
ISE @ ise @ KMA2007 | Serial | 811 | ||
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| Author | V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich | ||||
| Title | Pattern Recognition of Fragmented Objects with Adaptive Correlation Filters | Type | Miscellaneous | ||
| Year | 2006 | Publication | Topical Meeting on Optoinformatics / Information Photonics, 150–151 | Abbreviated Journal | |
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| Address | Saint-Petersburg (Russia) | ||||
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| Notes | ISE | Approved | no | ||
| Call Number |
ISE @ ise @ KMA2006b | Serial | 674 | ||
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| Author | V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich | ||||
| Title | Adaptive Correlation Filters for Pattern Recognition | Type | Journal | ||
| Year | 2006 | Publication | Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 16 | Issue | 3 | Pages | 425-431 |
| Keywords | Pattern recognition, Correlation filters, A adaptive filters | ||||
| Abstract | Adaptive correlation filters based on synthetic discriminant functions (SDFs) for reliable pattern recognition are proposed. A given value of discrimination capability can be achieved by adapting a SDF filter to the input scene. This can be done by iterative training. Computer simulation results obtained with the proposed filters are compared with those of various correlation filters in terms of recognition performance. | ||||
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| Notes | ISE | Approved | no | ||
| Call Number |
ISE @ ise @ KMA2006a | Serial | 673 | ||
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| Author | Ivan Huerta | ||||
| Title | Foreground Object Segmentation and Shadow Detection for Video Sequences in Uncontrolled Environments | Type | Book Whole | ||
| Year | 2010 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | This Thesis is mainly divided in two parts. The first one presents a study of motion
segmentation problems. Based on this study, a novel algorithm for mobile-object segmentation from a static background scene is also presented. This approach is demonstrated robust and accurate under most of the common problems in motion segmentation. The second one tackles the problem of shadows in depth. Firstly, a bottom-up approach based on a chromatic shadow detector is presented to deal with umbra shadows. Secondly, a top-down approach based on a tracking system has been developed in order to enhance the chromatic shadow detection. In our first contribution, a case analysis of motion segmentation problems is presented by taking into account the problems associated with different cues, namely colour, edge and intensity. Our second contribution is a hybrid architecture which handles the main problems observed in such a case analysis, by fusing (i) the knowledge from these three cues and (ii) a temporal difference algorithm. On the one hand, we enhance the colour and edge models to solve both global/local illumination changes (shadows and highlights) and camouflage in intensity. In addition, local information is exploited to cope with a very challenging problem such as the camouflage in chroma. On the other hand, the intensity cue is also applied when colour and edge cues are not available, such as when beyond the dynamic range. Additionally, temporal difference is included to segment motion when these three cues are not available, such as that background not visible during the training period. Lastly, the approach is enhanced for allowing ghost detection. As a result, our approach obtains very accurate and robust motion segmentation in both indoor and outdoor scenarios, as quantitatively and qualitatively demonstrated in the experimental results, by comparing our approach with most best-known state-of-the-art approaches. Motion Segmentation has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. Firstly, a bottom-up approach for detection and removal of chromatic moving shadows in surveillance scenarios is proposed. Secondly, a top-down approach based on kalman filters to detect and track shadows has been developed in order to enhance the chromatic shadow detection. In the Bottom-up part, the shadow detection approach applies a novel technique based on gradient and colour models for separating chromatic moving shadows from moving objects. Well-known colour and gradient models are extended and improved into an invariant colour cone model and an invariant gradient model, respectively, to perform automatic segmentation while detecting potential shadows. Hereafter, the regions corresponding to potential shadows are grouped by considering ”a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between local gradient structures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. In the top-down process, after detection of objects and shadows both are tracked using Kalman filters, in order to enhance the chromatic shadow detection, when it fails to detect a shadow. Firstly, this implies a data association between the blobs (foreground and shadow) and Kalman filters. Secondly, an event analysis of the different data association cases is performed, and occlusion handling is managed by a Probabilistic Appearance Model (PAM). Based on this association, temporal consistency is looked for the association between foregrounds and shadows and their respective Kalman Filters. From this association several cases are studied, as a result lost chromatic shadows are correctly detected. Finally, the tracking results are used as feedback to improve the shadow and object detection. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions. |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Gonzalez;Xavier Roca | |
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| ISSN | ISBN | 978-84-937261-3-3 | Medium | ||
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| Notes | Approved | no | |||
| Call Number |
ISE @ ise @ Hue2010 | Serial | 1332 | ||
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| Author | Ivan Huerta | ||||
| Title | Image-Sequence Segmentation in Uncontrolled Environments | Type | Report | ||
| Year | 2007 | Publication | CVC Technical Report #115 | Abbreviated Journal | |
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| Address | CVC (UAB) | ||||
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| Notes | Approved | no | |||
| Call Number |
ISE @ ise @ Hue2007 | Serial | 827 | ||
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| Author | Ivan Huerta; Dani Rowe; Mikhail Mozerov; Jordi Gonzalez | ||||
| Title | Improving Background Subtraction based on a Casuistry of Colour-Motion Segmentation Problems | Type | Book Chapter | ||
| Year | 2007 | Publication | 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:475–482 | Abbreviated Journal | |
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| Address | Girona (Spain) | ||||
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| Notes | ISE | Approved | no | ||
| Call Number |
ISE @ ise @ HRM2007 | Serial | 783 | ||
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| Author | Ivan Huerta; Dani Rowe; Jordi Gonzalez; Juan J. Villanueva | ||||
| Title | Efficient Incorporation of Motionless Foreground Objects for Adaptive Background Segmentation | Type | Book Chapter | ||
| Year | 2006 | Publication | IV Conference on Articulated Motion and Deformable Objects (AMDO´06), LNCS 4069: 424–433 | Abbreviated Journal | |
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| Address | Mallorca (Spain) | ||||
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| Notes | Approved | no | |||
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ISE @ ise @ HRG2006a | Serial | 702 | ||
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| Author | Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez | ||||
| Title | Detection and Removal of Chromatic Moving Shadows in Surveillance Scenarios | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 1499 - 1506 | ||
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| Abstract | Segmentation in the surveillance domain has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. In this paper we present a novel technique based on gradient and colour models for separating chromatic moving cast shadows from detected moving objects. Firstly, both a chromatic invariant colour cone model and an invariant gradient model are built to perform automatic segmentation while detecting potential shadows. In a second step, regions corresponding to potential shadows are grouped by considering “a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions. | ||||
| Address | Kyoto, Japan | ||||
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| ISSN | 1550-5499 | ISBN | 978-1-4244-4420-5 | Medium | |
| Area | Expedition | Conference | ICCV | ||
| Notes | Approved | no | |||
| Call Number |
ISE @ ise @ HHM2009 | Serial | 1213 | ||
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| Author | Ivan Huerta; Ariel Amato; Jordi Gonzalez; Juan J. Villanueva | ||||
| Title | Fusing Edge Cues to Handle Colour Problems in Image Segmentation | Type | Book Chapter | ||
| Year | 2008 | Publication | Articulated Motion and Deformable Objects, 5th International Conference | Abbreviated Journal | |
| Volume | 5098 | Issue | Pages | 279–288 | |
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| Address | Port d'Andratx (Mallorca) | ||||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| Area | Expedition | Conference | AMDO | ||
| Notes | ISE | Approved | no | ||
| Call Number |
ISE @ ise @ HAG2008 | Serial | 973 | ||
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| Author | Jordi Gonzalez; X. Varona; Juan J. Villanueva; Xavier Roca | ||||
| Title | On-line Human Activity Recognition for Video Surveillance. | Type | Miscellaneous | ||
| Year | 2001 | Publication | Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, 2:255–260. | Abbreviated Journal | |
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ISE @ ise @ GVV2001 | Serial | 111 | ||
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| Author | Jordi Gonzalez; J. Varona; Xavier Roca; Juan J. Villanueva | ||||
| Title | A Comparison Framework for Walking Performances using aSpaces | Type | Journal | ||
| Year | 2005 | Publication | Electronic Letters on Computer Vision and Image Analysis, Special Issue on articulated Motion, 5(3):105–116 (Electronic Letters: IF: 1.016) | Abbreviated Journal | |
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| Notes | ISE | Approved | no | ||
| Call Number |
ISE @ ise @ GVR2005 | Serial | 623 | ||
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