Direction Estimation of Pedestrian from Multiple Still Images
TOYOTA ODAIBA LAB TOKYO (JAPAN)
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The capability of estimating the walking direction of pedestrian would be useful in many applications such as those involving autonomous vehicles. We introduce an approach for estimating the walking direction of pedestrian 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.
- Optical Detection and Detectors