A biologically inspired system for human posture recognition

Shoushun Chen, Polina Akselrod, Eugenio Culurciello
2009 2009 IEEE Biomedical Circuits and Systems Conference  
We present a biologically-motivated system to recognize human postures in realtime video sequences. The system employs event-based temporal difference image between video sequences as input and builds a network of bio-inspired Gaborlike filters to detect contours of the active object. The detected contours are organized into vectorial line segments. After feature extraction, a classifier based on simplified line segment Hausdorff distance combined with projection histograms is implemented to
more » ... ieve size and position invariant recognition. 86% average recognition rate is achieved in the experiment. Compared to state-of-the art bio-inspired categorization methods shows great computational savings, and is an ideal candidate for hardware implementation with event-based circuits.
doi:10.1109/biocas.2009.5372070 fatcat:hddiu3sg3bgbdlajngw4vqlouu