Parallel algorithm implementation for multi-object tracking and surveillance
| Autor: | Nasreddine Taleb, Mohamed Elbahri, Kidiyo Kpalma, Joseph Ronsin |
|---|---|
| Přispěvatelé: | Université Djilali Liabès [Sidi-Bel-Abbès], Institut d'Électronique et des Technologies du numéRique (IETR), Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées Rouen, United Technologies, Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes 1 (UR1) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Computer science
Parallel algorithm Graphics processing unit CUDA 02 engineering and technology multi-object tracking surbveillance 0202 electrical engineering electronic engineering information engineering Computer vision Parallel OMP Parallel implementation Contextual image classification business.industry Cognitive neuroscience of visual object recognition 020206 networking & telecommunications Pattern recognition Sparse approximation Matching pursuit Feature (computer vision) Video tracking 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence business [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing Software |
| Zdroj: | IET Computer Vision IET Computer Vision, IET, 2016, 10 (3), pp.202-211. ⟨10.1049/iet-cvi.2015.0115⟩ IET Computer Vision, 2016, 10 (3), pp.202-211. ⟨10.1049/iet-cvi.2015.0115⟩ |
| ISSN: | 1751-9632 1751-9640 |
| DOI: | 10.1049/iet-cvi.2015.0115⟩ |
| Popis: | International audience; A recently developed sparse representation algorithm, has been proved to be useful for multi-object tracking and this study is a proposal for developing its parallelisation. An online dictionary learning is used for object recognition. After detection, each moving object is represented by a descriptor containing its appearance features and its position feature. Any detected object is classified and indexed according to the sparse solution obtained by an orthogonal matching pursuit (OMP) algorithm. For a real-time tracking, the visual information needs to be processed very fast without reducing the results accuracy. However, both the large size of the descriptor and the growth of the dictionary after each detection, slow down the system process. In this work, a novel accelerating OMP algorithm implementation on a graphics processing unit is proposed. Experimental results demonstrate the efficiency of the parallel implementation of the used algorithm by significantly reducing the computation time. |
| Databáze: | OpenAIRE |
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