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ICPR
2008
IEEE

Human action recognition with line and flow histograms

9 years 8 months ago
Human action recognition with line and flow histograms
We present a compact representation for human action recognition in videos using line and optical flow histograms. We introduce a new shape descriptor based on the distribution of lines which are fitted to boundaries of human figures. By using an entropy-based approach, we apply feature selection to densify our feature representation, thus, minimizing classification time without degrading accuracy. We also use a compact representation of optical flow for motion information. Using line and flow histograms together with global velocity information, we show that high-accuracy action recognition is possible, even in challenging recording conditions. 1
Nazli Ikizler, Pinar Duygulu, Ramazan Gokberk Cinb
Added 05 Nov 2009
Updated 05 Nov 2009
Type Conference
Year 2008
Where ICPR
Authors Nazli Ikizler, Pinar Duygulu, Ramazan Gokberk Cinbis
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