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| Author | Agnes Borras; Josep Llados | ||||
| Title | Object Image Retrieval by Shape Content in Complex Scenes Using Geometric Constraints | Type | Book Chapter | ||
| Year | 2005 | Publication | Pattern Recognition And Image Analysis | Abbreviated Journal | LNCS |
| Volume | 3522 | Issue | Pages | 325–332 | |
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| Abstract | This paper presents an image retrieval system based on 2D shape information. Query shape objects and database images are repre- sented by polygonal approximations of their contours. Afterwards they are encoded, using geometric features, in terms of predefined structures. Shapes are then located in database images by a voting procedure on the spatial domain. Then an alignment matching provides a probability value to rank de database image in the retrieval result. The method al- lows to detect a query object in database images even when they contain complex scenes. Also the shape matching tolerates partial occlusions and affine transformations as translation, rotation or scaling. | ||||
| Address | Estoril (Portugal) | ||||
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| Publisher | Springer Link | Place of Publication | Editor | ||
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| Notes | DAG; | Approved | no | ||
| Call Number | DAG @ dag @ BoL2005; IAM @ iam @ BoL2005 | Serial | 556 | ||
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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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ISBN | Medium | |||
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| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ KMA2006a | Serial | 673 | ||
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| Author | E. Tavalera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva | ||||
| Title | Regularized Clustering for Egocentric Video Segmentation | Type | Book Chapter | ||
| Year | 2015 | Publication | Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | Issue | Pages | 327-336 | ||
| Keywords | Temporal video segmentation ; Egocentric videos ; Clustering | ||||
| Abstract | In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energyminimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate techniques in an energy-minimization framework that serves disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods. | ||||
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| Publisher | Springer International Publishing | Place of Publication | Editor | ||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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ISBN | 978-3-319-19390-8 | Medium | ||
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| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @TDB2015a | Serial | 2781 | ||
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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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