Person Reidentification Based on Multiscale Convolutional Feature Fusion

Longzhuang Xu; Li Peng

doi:10.3788/LOP56.141504

Laser & Optoelectronics Progress, Volume. 56, Issue 14, 141504(2019)

Person Reidentification Based on Multiscale Convolutional Feature Fusion

Longzhuang Xu and Li Peng^*

Engineering Research Center of Internet of Things Technology Applications of the Ministry of Education, School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China

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Abstract Get PDF(in Chinese)

Figures & Tables(7)

Fig. 1. Network structure

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Fig. 2. Comparison of our blocking strategy with PCB blocking strategy

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Fig. 3. Geometric diagram of the second classification. (a) Original softmax loss; (b) softmax loss with normalized weights and features

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Fig. 4. Results of recognition algorithm. (a) Baseline; (b) PCB (out RPP); (c) baseline+SPP (1+2+6); (d) ours

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Table 1. Effects of two methods for improving baseline model

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Table 1. Effects of two methods for improving baseline model

Model	Market-1501		DukeMTMC-reID
Model	rank-1	mAP	rank-1	mAP
Baseline	86.88	69.59	72.62	54.93
Baseline+SPP	89.31	71.41	80.83	64.99
Baseline+L2_softmax	88.72	72.42	76.93	60.18
Ours	91.36	75.46	82.05	65.97
Ours+Re-ranking	93.29	88.81	86.49	81.93

Table 2. Performance comparison of different block models

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Table 2. Performance comparison of different block models

Model	Market-1501		DukeMTMC-reID
Model	rank-1	mAP	rank-1	mAP
Baseline	86.88	69.59	72.62	54.93
PCB(out RPP)	88.48	69.89	80.21	64.27
Baseline+SPP(1+2+3)	89.31	71.41	80.83	64.99
Baseline+SPP(1+2+4)	89.41	70.68	79.35	62.55
Baseline+SPP(1+2+6)	88.09	68.75	80.05	64.89

Table 3. Performance comparison of our algorithm with mainstream algorithms

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Table 3. Performance comparison of our algorithm with mainstream algorithms

Method	Market-1501		DukeMTMC-reID
Method	rank-1	mAP	rank-1	mAP
PSE	87.7	69.0	79.8	62.0
GLAD	89.9	73.9	—	—
SVDNet	82.3	62.1	76.7	56.8
MultiScale	88.9	73.1	79.2	60.6
MLFN	90.0	74.3	81.0	62.8
HA-CNN	91.2	75.7	80.5	63.8
DPFL	88.9	72.6	79.2	60.6
Ours	91.4	75.5	82.1	66.0
Ours+Re-ranking	93.3	88.9	86.5	81.9

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Longzhuang Xu, Li Peng. Person Reidentification Based on Multiscale Convolutional Feature Fusion[J]. Laser & Optoelectronics Progress, 2019, 56(14): 141504

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Paper Information

Category: Machine Vision

Received: Jan. 4, 2019

Accepted: Feb. 26, 2019

Published Online: Jul. 12, 2019

The Author Email: Peng Li (pengli@jiangnan.edu.cn)

DOI:10.3788/LOP56.141504

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology