Walking pedestrian recognition
Curio, C.
Edelbrunner, J.
Kalinke, T.
Tzomakas, C.
von Seelen, W.
Pattern Recognition & Sci. Anal. Group, Ruhr-Univ., Bochum;
This paper appears in: Intelligent Transportation Systems, IEEE Transactions on
Publication Date: Sep 2000
Volume: 01,
Issue: 3
On page(s): 155-163
ISSN: 1524-9050
References Cited: 23
CODEN: ITISFG
INSPEC Accession Number: 6808490
Digital Object Identifier: 10.1109/6979.892152
Current Version Published: 2002-08-06
Abstract
In previous 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 the paper, a method for the
detection, tracking, and final recognition of pedestrians crossing the
moving observer'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 quasirigid 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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