| 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 |
