Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/91595
Title: A biologically inspired system for human posture recognition
Authors: Chen, Shoushun
Akselrod, Polina
Culurciello, Eugenio
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2009
Source: Chen, S. S., Akselrod, P., & Culurciello, E. (2009). A biologically inspired system for human posture recognition. In proceedings of the IEEE Biomedical Circuits and Systems Conference: Beijing, China, (pp.113-116).
Abstract: 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 achieve 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.
URI: https://hdl.handle.net/10356/91595
http://hdl.handle.net/10220/6362
DOI: http://dx.doi.org/10.1109/BIOCAS.2009.5372070
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Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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