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  Walking Pedestrian Recognition

Curio, C., Edelbrunner, J., Kalinke, T., Tzomakas, C., & von Seelen, W. (2000). Walking Pedestrian Recognition. IEEE Transactions on Intelligent Transportation Systems, 1(3), 155-163. doi:10.1109/6979.892152.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-E45F-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-187D-7
Genre: Journal Article

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 Creators:
Curio, C1, Author              
Edelbrunner, J, Author
Kalinke, T, Author
Tzomakas, C, Author
von Seelen, W, Author
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1External Organizations, ou_persistent22              

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 Abstract: In recent years many methods providing the ability to recognize rigid obstacles - sedans and trucks - have been developed. These methods provide the driver with relevant information. They are able to cope reliably with scenarios on motorways. Nevertheless, not much attention has been given to image processing approaches to increase the safety of pedestrians in urban environments. In this paper a method for the detection, tracking, and final recognition of pedestrians crossing the moving oberserver‘s trajectory is suggested. A combination of data- and model-driven approaches is realized. The initial detection process is based on a fusion of texture analysis, model-based grouping of, most likely, the geometric features of pedestrians, and inverse-perspective mapping (binocular vision). Additionally, motion patterns of limb movements are analyzed to determine initial object hypotheses. The tracking of the quasi-rigid part of the body is performed by different algorithms that have been successfully employed for the tracking of sedans, trucks, motorbikes, and pedestrians. The final classification is obtained by a temporal analysis of the walking process

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 Dates: 2000-09
 Publication Status: Published in print
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 Rev. Type: -
 Identifiers: DOI: 10.1109/6979.892152
BibTex Citekey: 2572
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Title: IEEE Transactions on Intelligent Transportation Systems
Source Genre: Journal
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Pages: - Volume / Issue: 1 (3) Sequence Number: - Start / End Page: 155 - 163 Identifier: -