TY - GEN
T1 - Local trinary patterns for human action recognition
AU - Yeffet, Lahav
AU - Wolf, Lior
PY - 2009
Y1 - 2009
N2 - We present a novel action recognition method which is based on combining the effective description properties of Local Binary Patterns with the appearance invariance and adaptability of patch matching based methods. The resulting method is extremely efficient, and thus is suitable for real-time uses of simultaneous recovery of human action of several lengths and starting points. Tested on all publicity available datasets in the literature known to us, our system repeatedly achieves state of the art performance. Lastly, we present a new benchmark that focuses on uncut motion recognition in broadcast sports video.
AB - We present a novel action recognition method which is based on combining the effective description properties of Local Binary Patterns with the appearance invariance and adaptability of patch matching based methods. The resulting method is extremely efficient, and thus is suitable for real-time uses of simultaneous recovery of human action of several lengths and starting points. Tested on all publicity available datasets in the literature known to us, our system repeatedly achieves state of the art performance. Lastly, we present a new benchmark that focuses on uncut motion recognition in broadcast sports video.
UR - http://www.scopus.com/inward/record.url?scp=77953205594&partnerID=8YFLogxK
U2 - 10.1109/ICCV.2009.5459201
DO - 10.1109/ICCV.2009.5459201
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AN - SCOPUS:77953205594
SN - 9781424444205
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 492
EP - 497
BT - 2009 IEEE 12th International Conference on Computer Vision, ICCV 2009
T2 - 12th International Conference on Computer Vision, ICCV 2009
Y2 - 29 September 2009 through 2 October 2009
ER -