Abstract
This paper presents BB6-HM, a block-based human model for real-time monitoring of a large number of visual events and states related to human activity analysis, which can be used as components of a library to describe more complex activities in such important areas as surveillance. BB6-HM is inspired by the proportionality rules commonly used in Visual Arts, i.e., for dividing the human silhouette into six rectangles of the same height. The major advantage of this proposal is that analysis of the human can be easily broken down into parts, which allows us to introduce more specific domain knowledge and to reduce the computational load. It embraces both frontal and lateral views, is a fast and scale-invariant method and a large amount of task-focused information can be extracted from it.
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References
Ben-Arie, J., Wang, Z., Pandit, P., Rajaram, S.: Human Activity Recognition Using Multidimensional Indexing. IEEE Trans. on Pattern Analysis and machine Intelligence 24(8), 1091–1104 (2002)
Carmona, E.J., Martínez-Cantos, J., Mira, J.: A new video segmentation method of moving objects based on blob-level knowledge. Pattern Recognition Letters 29(3), 272–285 (2008)
Carmona, E.J., Rincón, M., Bachiller, M., Martínez-Cantos, J., Martinez-Tomas, R., Mira, J.: On the effect of feedback in multilevel representation spaces for visual surveillance tasks. Neurocomputing 72(4-6), 916–927 (2009)
Gavrila, D.: The Visual Analysis of Human Movement: A Survey. Computer Vision and Image Understanding 73(1), 82–98 (1999)
Haritaoglu, I., Harwood, D., Davis, L.S.: W4: Real-Time Surveillance of People and Their Activities. IEEE Trans. on Pattern Analysis and machine Intelligence 22(8), 809–830 (2000)
Martinez-Tomas, R., Rincón, M., Bachiller, M., Mira, J.: On the Correspondence between Objects and Events for the Diagnosis of Situations in Visual Surveillance Tasks. Pattern Recognition Letters 29(8), 1117–1135 (2008)
Wren, C.R., Azarbayejani, A., Darrell, T., Pentland, A.P.: Pfinder: Real-Time Tracking of the Human Body. IEEE Trans. on Pattern Analysis and machine Intelligence 19(7), 780–785 (1997)
Zhang, J., Collins, R., Liu, Y.: Representation and Matching of Articulated Shapes. In: International Conference on Computer Vision and Pattern Recognition, pp. 342–349 (2004)
Zhao, T., Nevatia, R.: Tracking Multiple Humans in Complex Situations. IEEE Trans. on Pattern Analysis and machine Intelligence 26(9), 1208–1221 (2004)
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Folgado, E., Rincón, M., Bachiller, M., Carmona, E.J. (2009). A Block-Based Human Model for Visual Surveillance. In: Mira, J., Ferrández, J.M., Álvarez, J.R., de la Paz, F., Toledo, F.J. (eds) Bioinspired Applications in Artificial and Natural Computation. IWINAC 2009. Lecture Notes in Computer Science, vol 5602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02267-8_23
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DOI: https://doi.org/10.1007/978-3-642-02267-8_23
Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-02267-8
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