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IJCV
2010

Volumetric Features for Video Event Detection

9 years 21 days ago
Volumetric Features for Video Event Detection
Real-world actions occur often in crowded, dynamic environments. This poses a difficult challenge for current approaches to video event detection because it is difficult to segment the actor from the background due to distracting motion from other objects in the scene. We propose a technique for event recognition in crowded videos that reliably identifies actions in the presence of partial occlusion and background clutter. Our approach is based on three key ideas: (1) we efficiently match the volumetric representation of an event against oversegmented spatio-temporal video volumes; (2) we augment our shape-based features using flow; (3) rather than treating an event template as an atomic entity, we separately match by parts (both in space and time), enabling robustness against occlusions and actor variability. Our experiments on human actions, such as picking up a dropped object or waving in a crowd show reliable detection with few false positives.
Yan Ke, Rahul Sukthankar, Martial Hebert
Added 27 Jan 2011
Updated 27 Jan 2011
Type Journal
Year 2010
Where IJCV
Authors Yan Ke, Rahul Sukthankar, Martial Hebert
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