Learning Spatiotemporal Graphs of Human Activities

7 years 5 months ago
Learning Spatiotemporal Graphs of Human Activities
Complex human activities occurring in videos can be defined in terms of temporal configurations of primitive actions. Prior work typically hand-picks the primitives, their total number, and temporal relations (e.g., allow only followed-by), and then only estimates their relative significance for activity recognition. We advance prior work by learning what activity parts and their spatiotemporal relations should be captured to represent the activity, and how relevant they are for enabling efficient inference in realistic videos. We represent videos by spatiotemporal graphs, where nodes correspond to multiscale video segments, and edges capture their hierarchical, temporal, and spatial relationships. Access to video segments is provided by our new, multiscale segmenter. Given a set of training spatiotemporal graphs, we learn their archetype graph, and pdf’s associated with model nodes and edges. The model adaptively learns from data relevant video segments and their relations, addr...
William Brendel, Sinisa Todorovic
Added 11 Dec 2011
Updated 11 Dec 2011
Type Journal
Year 2011
Where ICCV
Authors William Brendel, Sinisa Todorovic
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