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Direction Estimation of Pedestrian from Images

Author(s)
Shimizu, Hiroaki; Poggio, Tomaso
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Abstract
The capability of estimating the walking direction of people would be useful in many applications such as those involving autonomous cars and robots. We introduce an approach for estimating the walking direction of people from images, based on learning the correct classification of a still image by using SVMs. We find that the performance of the system can be improved by classifying each image of a walking sequence and combining the outputs of the classifier. Experiments were performed to evaluate our system and estimate the trade-off between number of images in walking sequences and performance.
Date issued
2003-08-27
URI
http://hdl.handle.net/1721.1/7277
Other identifiers
AIM-2003-020
CBCL-230
Series/Report no.
AIM-2003-020CBCL-230
Keywords
AI, pedestrian, walking direction, classification, SVM, recognition, human motion

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