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ICCV
2009
IEEE

Selection and context for action recognition

8 years 3 months ago
Selection and context for action recognition
Recognizing human action in non-instrumented video is a challenging task not only because of the variability produced by general scene factors like illumination, background, occlusion or intra-class variability, but also because of subtle behavioral patterns among interacting people or between people and objects in images. To improve recognition, a system may need to use not only low-level spatio-temporal video correlations but also relational descriptors between people and objects in the scene. In this paper we present contextual scene descriptors and Bayesian multiple kernel learning methods for recognizing human action in complex non-instrumented video. Our contribution is threefold: (1) we introduce bag-of-detector scene descriptors that encode presence/absence and structural relations between object parts; (2) we derive a novel Bayesian classification method based on Gaussian processes with multiple kernel covariance functions (MKGPC), in order to automatically select and weight ...
Dong Han, Liefeng Bo, Cristian Sminchisescu
Added 18 Feb 2011
Updated 18 Feb 2011
Type Journal
Year 2009
Where ICCV
Authors Dong Han, Liefeng Bo, Cristian Sminchisescu
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