Indirect Person Re-identification Based on Support Samples

SUN Rui; FANG Wei; HUANG Qiheng; GAO Jun

doi:10.11999/JEIT170215

Volume 39 Issue 12

Dec. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(12): 2953-2961

SUN Rui, FANG Wei, HUANG Qiheng, GAO Jun. Indirect Person Re-identification Based on Support Samples[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2953-2961. doi: 10.11999/JEIT170215

Citation:

SUN Rui, FANG Wei, HUANG Qiheng, GAO Jun. Indirect Person Re-identification Based on Support Samples[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2953-2961. doi: 10.11999/JEIT170215

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Indirect Person Re-identification Based on Support Samples

doi: 10.11999/JEIT170215

Funds:

The National Natural Science Foundation of China (61471154), Anhui Province Science and Technology Research (170d0802181)

Received Date: 2017-03-17
Rev Recd Date: 2017-09-15
Publish Date: 2017-12-19

Abstract

Abstract

Person re-identification is the identification of the same pedestrian in a multi camera surveillance without overlapping views. Aiming at the problem of the existence of visual angle, illumination and scale change in pedestrian images which from different camera. An indirect person re-identification method is proposed based on the support samples. At first, the algorithm extracts the support samples from different cameras by the clustering method. When it comes to matching pedestrians from different cameras, the support samples are used to distinguish the pedestrians categories under the camera on the basis of the distance metric, by comparing the categories to determine whether the same pedestrian. The method avoids the direct matching of pedestrian images under different cameras, which effectively solve the problem of the existence of visual angle, illumination and scale change in different camera. The experimental results show that the algorithm has a high recognition rate, and on the data set VIPeR, CAVIAR4ReID and CUHK01the, Rank1 reaches 43.60%, 41.36% and 43.82% respectively.
- Person re-identification,
- Support samples,
- Indirect matching

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References(31)

References

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