Pedestrian Detection and Range Estimation Based on CENTRIST Descriptor and Implementation
碩士 === 國立臺灣大學 === 資訊工程學研究所 === 100 === A method of pedestrian detection and range estimation based on CENTRIST descriptor is proposed in this thesis. In related work such as C4 human detection method [7], the CENTRIST descriptor uses only features in a fixed scale, which may omit the features of lar...
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| Format: | Others |
| Language: | en_US |
| Published: |
2011
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| Online Access: | http://ndltd.ncl.edu.tw/handle/30998585945104187583 |
| Summary: | 碩士 === 國立臺灣大學 === 資訊工程學研究所 === 100 === A method of pedestrian detection and range estimation based on CENTRIST descriptor is proposed in this thesis. In related work such as C4 human detection method [7], the CENTRIST descriptor uses only features in a fixed scale, which may omit the features of larger or global structures. In our work, four different settings of the sizes of the superblocks are adopted to overcome such problem. We use Daimler Pedestrian Detection Benchmark [2] to train SVM models and to evaluate the performance. Our experimental results show that our proposed method outperforms C4 human detection method in false alarms with comparable accuracy. Our proposed method is not only easy to implement but also friendly for hardware acceleration and the performance can be better if geometric or stereo information can be accessed.
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