Object Detection with Vocabularies of Space-time Descriptors
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| Format: | Artículo científico |
| Language: | en |
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Universidad Nacional Autónoma de México
2012
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| _version_ | 1876488859514044416 |
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| author | Y. Hernandez-Heredia |
| author_facet | Y. Hernandez-Heredia |
| contents | Object Detection with Vocabularies of Space-time Descriptors Y. Hernandez-Heredia J.M.a González-Linares N. Guil J. Ortiz R. Hernandez J.R. Cózar Ingeniería vocabulary Object detection binary classifier video segmentation This paper presents a novel framework for objects detection in security and broadcast videos. Our method assumes that object classes are unknown in advance and exploit the temporal-space properties of the videos for the creation of a vocabulary that describes these classes. Local space-time features have recently became a popular video representation for action recognition and object detection. Several methods for feature localization and description have been proposed in the literature and promising recognition results were demonstrated for a number of action classes. In this work we propose the use of different kinds of descriptors for the creation of vocabularies for different detection object task. For a better description of the videos we carry out a background model, tryring to clean up and follow the areas where there are objects. The points of interest in the videos to characterize the objects are calculated with a temporary variant of the famous Harris corner detector. With the descriptors obtained from the points of interest, a vocabulary is realized usingthe kinds of videos we want to train. Then we obtained the frequency histograms between the videos for training and the vocabulary so, with a binary classifier obtain the trained classes and following the same procedure without the vocabulary realized the detection and monitoring of the objects. The new method presented is also compared with a state of the art method, obtaining better results in both accuracy and false object rejection. 2012 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47425142015 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.6 Vol.10 |
| format | Artículo científico |
| id | redalyc_47425142015 |
| institution | Redalyc |
| language | en |
| publishDate | 2012 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Object Detection with Vocabularies of Space-time Descriptors Y. Hernandez-Heredia Ingeniería vocabulary Object detection binary classifier video segmentation Object Detection with Vocabularies of Space-time Descriptors Y. Hernandez-Heredia J.M.a González-Linares N. Guil J. Ortiz R. Hernandez J.R. Cózar Ingeniería vocabulary Object detection binary classifier video segmentation This paper presents a novel framework for objects detection in security and broadcast videos. Our method assumes that object classes are unknown in advance and exploit the temporal-space properties of the videos for the creation of a vocabulary that describes these classes. Local space-time features have recently became a popular video representation for action recognition and object detection. Several methods for feature localization and description have been proposed in the literature and promising recognition results were demonstrated for a number of action classes. In this work we propose the use of different kinds of descriptors for the creation of vocabularies for different detection object task. For a better description of the videos we carry out a background model, tryring to clean up and follow the areas where there are objects. The points of interest in the videos to characterize the objects are calculated with a temporary variant of the famous Harris corner detector. With the descriptors obtained from the points of interest, a vocabulary is realized usingthe kinds of videos we want to train. Then we obtained the frequency histograms between the videos for training and the vocabulary so, with a binary classifier obtain the trained classes and following the same procedure without the vocabulary realized the detection and monitoring of the objects. The new method presented is also compared with a state of the art method, obtaining better results in both accuracy and false object rejection. 2012 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47425142015 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.6 Vol.10 |
| title | Object Detection with Vocabularies of Space-time Descriptors |
| topic | Ingeniería vocabulary Object detection binary classifier video segmentation |
| url | https://www.redalyc.org/articulo.oa?id=47425142015 |