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A bio-inspired event-based size and position invariant human posture recognition algorithm.

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A bio-inspired event-based size and position invariant human posture recognition algorithm.

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dc.contributor.author Chen, Shoushun.
dc.contributor.author Martini, Berin.
dc.contributor.author Culurciello, Eugenio.
dc.date.accessioned 2010-08-30T05:54:52Z
dc.date.available 2010-08-30T05:54:52Z
dc.date.copyright 2009
dc.date.issued 2010-08-30T05:54:52Z
dc.identifier.citation Chen, S. S., Martini, B., & Culurciello, E. (2009). A bio-inspired event-based size and position invariant human posture recognition algorithm. In proceedings of the IEEE International Symposium on Circuits and Systems: Taipei, Taiwan, (pp.775-778).
dc.identifier.uri http://hdl.handle.net/10220/6363
dc.description.abstract This paper proposes a new approach to recognize human postures in realtime video sequences. 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. Consistent with the hierarchical model of the human visual system, sub-sampling techniques are used to represent the object by line segments at multiple resolution levels. The whole classification is described as a coarse to fine procedure. An average realtime recognition rate of 88% is achieved in the experiment. Compared to conventional convolution method, the proposed algorithm reduces the computation cycles by 10 − 100 times. This work sets the foundation for size and position invariant object recognition for the implementation of eventbased vision systems
dc.format.extent 4 p.
dc.language.iso en
dc.rights © 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. http://www.ieee.org/portal/site This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
dc.subject DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing.
dc.title A bio-inspired event-based size and position invariant human posture recognition algorithm.
dc.type Conference Paper
dc.contributor.conference IEEE International Symposium on Circuits and Systems (2009 : Taipei, Taiwan)
dc.contributor.school School of Electrical and Electronic Engineering
dc.identifier.doi http://dx.doi.org/10.1109/ISCAS.2009.5117864
dc.description.version Published version

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