Title :
Live demonstration: A bio-inspired event-based size and position invariant human posture recognition algorithm
Author :
Chen, Shoushun ; Martini, Berin ; Culurciello, Eugenio
Author_Institution :
Electr. Eng. Dept., Yale Univ., New Haven, CT, USA
Abstract :
We demonstrate a realtime human postures recognition platform. The algorithm employs temporal difference imaging between video sequences as input and then decompose the contour of the active object into vectorial line segments. A scheme based on simplified line segment Hausdorff distance combined with projection histograms is proposed to achieve size and position invariance recognition. Inspired by the hierarchical model of human visual system, the whole classification is described as a coarse to fine procedure. 88% average realtime recognition rate is achieved in the experiment.
Keywords :
image sequences; object recognition; video signal processing; bio-inspired event-based position invariant; bio-inspired event-based size invariant; human posture recognition algorithm; human visual system; line segment Hausdorff distance; live demonstration; projection histograms; vectorial line segments; video sequences; Application software; CMOS image sensors; Cellular phones; Computed tomography; Computer displays; Hardware; Humans; Image segmentation; Image sensors; Visual system;
Conference_Titel :
Circuits and Systems, 2009. ISCAS 2009. IEEE International Symposium on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-3827-3
Electronic_ISBN :
978-1-4244-3828-0
DOI :
10.1109/ISCAS.2009.5117865
