Rapid Object Detection Algorithm Based on Deformable Part Models

LI Chunwei; YU Hongtao; LI Shaomei; BU Youjun

doi:10.11999/JEIT160080

Volume 38 Issue 11

Dec. 2016

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LI Chunwei, YU Hongtao, LI Shaomei, BU Youjun. Rapid Object Detection Algorithm Based on Deformable Part Models[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2864-2870. doi: 10.11999/JEIT160080

Citation:

LI Chunwei, YU Hongtao, LI Shaomei, BU Youjun. Rapid Object Detection Algorithm Based on Deformable Part Models[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2864-2870. doi: 10.11999/JEIT160080

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Rapid Object Detection Algorithm Based on Deformable Part Models

doi: 10.11999/JEIT160080

Funds:

The National Natural Science Foundation of China (61572519, 61521003)

Received Date: 2016-01-19
Rev Recd Date: 2016-06-08
Publish Date: 2016-11-19

Abstract

Abstract

To solve the speed bottleneck of deformable part models in the detection process, this paper proposes a cascade deformable part model with rapid computation of feature pyramids for the detection process of the model. Because the speed of the detection is mainly determined by the two processes of the feature computation and the object location, a two-stage speedup algorithm is proposed. Firstly, sparsely-sampled feature pyramids on the scale are utilized to approximate finely-sampled multi-scale image features to speed up the process of feature computation. Then combined with the cascade algorithm in the location process, a sequence model is utilized to evaluate individual parts sequentially so as to rapidly prune most object hypotheses of small possibilities in order to speed up the process of object location. The experimental results on PASCAL VOC 2007 dataset and INRIA dataset show that the algorithm in the paper apparently speeds up the speed of detection with minor loss in detection precision.
- Rapid object detection,
- Deformable part model,
- Feature computation,
- Cascade detection

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References(20)

References

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