Browse > Article
http://dx.doi.org/10.3837/tiis.2021.06.009

Vehicle Face Re-identification Based on Nonnegative Matrix Factorization with Time Difference Constraint  

Ma, Na (School of Business Administration, Liaoning Technical University)
Wen, Tingxin (School of Business Administration, Liaoning Technical University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.6, 2021 , pp. 2098-2114 More about this Journal
Abstract
Light intensity variation is one of the key factors which affect the accuracy of vehicle face re-identification, so in order to improve the robustness of vehicle face features to light intensity variation, a Nonnegative Matrix Factorization model with the constraint of image acquisition time difference is proposed. First, the original features vectors of all pairs of positive samples which are used for training are placed in two original feature matrices respectively, where the same columns of the two matrices represent the same vehicle; Then, the new features obtained after decomposition are divided into stable and variable features proportionally, where the constraints of intra-class similarity and inter-class difference are imposed on the stable feature, and the constraint of image acquisition time difference is imposed on the variable feature; At last, vehicle face matching is achieved through calculating the cosine distance of stable features. Experimental results show that the average False Reject Rate and the average False Accept Rate of the proposed algorithm can be reduced to 0.14 and 0.11 respectively on five different datasets, and even sometimes under the large difference of light intensities, the vehicle face image can be still recognized accurately, which verifies that the extracted features have good robustness to light variation.
Keywords
Vehicle face re-identification; Nonnegative Matrix Factorization; stable feature; variable feature; cosine distance;
Citations & Related Records
연도 인용수 순위
  • Reference
1 J. T. Wang, H. Zheng, Y. Huang and X. H. Ding, "Vehicle type recognition in surveillance images from labeled web-nature data using deep transfer learning," IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 9, pp. 2913-2922, 2018.   DOI
2 H. Wang, Y. J. Yu, Y. F. Chen and X. B. Chen, "A vehicle recognition algorithm based on deep transfer learning with a multiple feature subspace distribution," Sensors, vol. 18, no. 12, pp. 4109, 2018.   DOI
3 P. Khorramshahi, N. Peri, J. C. Chen and R. Chellappa, "The Devil is in the Details: Self-Supervised Attention for Vehicle Re-Identification," in Proc. of European Conference on Computer Vision, pp. 369-386, August 23-28, 2020.
4 X. Jia, F. M. Sun, H. J. Li and Y. D. Cao, "Hand Vein Recognition Algorithm Based on NMF with Sparsity and Clustering Property Constraints in Feature Mapping Space," Chinese Journal of Electronics, vol. 28, no. 6, pp. 1184-1190, 2019.   DOI
5 Y. H. Lou, Y. Bai, J. Liu, S. Q. Wang and L. Y. Duan, "VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild," in Proc. of IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3230-3238, June 15-20, 2019.
6 T. S. Chen, C. T. Liu, C. W. Wu and S. Y. Chien, "Orientation-aware Vehicle Re-identification with Semantics-guided Part Attention Network," in Proc. of European Conference on Computer Vision, pp. 330-346, August 23-28, 2020.
7 A. Q. Hu, H. Li, F. Zhang and W. Zhang, "Deep Boltzmann machines based vehicle recognition," in Proc. of Chinese Control and Decision Conference, pp. 3033-3038, May 31-June 2, 2014.
8 D. F. S. Santos, G. B. De Souza and A. N. Marana, "A 2D Deep Boltzmann Machine for robust and fast vehicle classification," in Proc. of SIBGRAPI Conference on Graphics, Patterns and Images, pp. 155-162, October 17-20, 2017.
9 X. Jin, C. L. Lan, W. J. Zeng and Z. B. Chen, "Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification," in Proc. of the AAAI Conference on Artificial Intelligence, pp. 11165-11172, February 7-12, 2020.
10 Z. D. Zheng, T. Ruan, Y. C. Wei, Y. Yang and T. Mei, "VehicleNet: Learning Robust Visual Representation for Vehicle Re-identification," IEEE Transactions on Multimedia, Early Access, 2020.
11 X. Jia, F. M. Sun, H. J. Li, Y. D. Cao and X. Zhang, "Image Multi-Label Annotation Based on Supervised Nonnegative Matrix Factorization with New Matching Measurement," Neurocomputing, vol. 219, pp. 518-525, 2017.   DOI
12 Z. Dong, Y. W. Wu, M. T. Pei and Y. D. Jia, "Vehicle Type Classification Using a Semisupervised Convolutional Neural Network," IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 4, pp. 2247-2256, 2015.   DOI
13 J. Sochor, A. Herout, and J. Havel, "Boxcars: 3d boxes as cnn input for improved fine-grained vehicle recognition," in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3006-3015, June 27-30, 2016.
14 Y. Y. Wu and C. M. Tsai, "Pedestrian, bike, motorcycle, and vehicle classification via deep learning: deep belief network and small training set," in Proc. of International Conference on Applied System Innovation, pp. 1-4, May 26-31, 2016.
15 X. B. Liu, S. L. Zhang, X. Y. Wang, R. C. Hong and Q. Tian, "Group-Group Loss-Based Global-Regional Feature Learning for Vehicle Re-Identification," IEEE Transactions on Image Processing, vol. 29, pp. 2638-2652, 2019.   DOI
16 C. H. Shi and C. D. Wu, "Vehicle Face Recognition Algorithm Based on Weighted Nonnegative Matrix Factorization with Double Regularization Terms," KSII Transactions on Internet and Information Systems, vol. 14, no. 5, pp. 2171-2185, 2020.   DOI
17 A. P. Psyllos, C. N. E. Anagnostopoulos and E. Kayafas, "Vehicle Logo Recognition Using a SIFT-Based Enhanced Matching Scheme," IEEE Transactions on Intelligent Transportation Systems, vol. 11, no. 2, pp. 322-328, 2010.   DOI
18 X. C. Liu, W. Liu, H. D. Ma and H. Y. Fu, "Large-scale vehicle re-identification in urban surveillance videos," in Proc. of IEEE International Conference on Multimedia and Expo, pp. 1-6, July 11-15, 2016.
19 H. Y. Liu, Y. H. Tian, Y. W. Wang, L. Pang and T. J. Huang, "Deep Relative Distance Learning: Tell the Difference between Similar Vehicles," in Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 2167-2175, June 27-30, 2016.
20 Y. Chen, C. Yang and S. Y. Yang, "A method for special vehicle recognition based on deep-transfer model," in Proc. of International Conference on Instrumentation & Measurement, Computer, Communication and Control, pp. 167-170, July 21-23, 2016.
21 J. Prokaj and G. Medioni, "3-D model based vehicle recognition," in Proc. of 2009 Workshop on Applications of Computer Vision, pp. 1-7, December 7-8, 2009.
22 X. JIA and F. M. SUN, "Vehicle face re-identification algorithm based on Siamese nonnegative matrix factorization," Chinese Journal of Scientific Instrument, vol. 41, no. 6, pp. 132-139, 2020.
23 K. J. Kim, S. M. Park and Y. J. Choi, "Deciding the number of color histogram bins for vehicle color recognition," in Proc. of Asia-Pacific Services Computing Conference, pp. 134-138, December 9-12, 2008.
24 P. Negri, X. Clady, M. Milgram and R. Poulenard, "An oriented-contour point based voting algorithm for vehicle type classification," in Proc. of International Conference on Pattern Recognition, pp. 574-577, August 20-24, 2006.
25 P. Chen, X. Bai and W. Liu, "Vehicle color recognition on urban road by feature context," IEEE Transactions on Intelligent Transportation Systems, vol. 15, no. 5, pp. 2340-2346, 2014.   DOI
26 W. W. L. Lam, C. C. C. Pang and N. H. C. Yung, "Vehicle-Component Identification Based on Multiscale Textural Couriers," IEEE Transactions on Intelligent Transportation Systems, vol. 8, no. 4, pp. 681-694, 2007.   DOI
27 K. Huang and B. Zhang, "Fine-grained vehicle recognition by deep Convolutional Neural Network," in Proc. of 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, pp. 465-470, October, 15-17, 2016.
28 W. Hai, Y. Cai and L Chen, "A Vehicle Detection Algorithm Based on Deep Belief Network," The Scientific World Journal, pp. 1-7, 2014.
29 C. Gou, K. F. Wang, Y. J. Yao and Z. X. Li, "Vehicle license plate recognition based on extremal regions and restricted Boltzmann machines," IEEE Transactions on Intelligent Transportation Systems, vol. 17, no. 4, pp. 1096-1107, 2015.   DOI
30 D. C. Meng, L. Li, X. J. Liu, Y. D. Li, S. J. Yang, Z. J. Zha, X. Y. Gao, S. H. Wang and Q. M. Huang, "Parsing-based View-aware Embedding Network for Vehicle Re-Identification," in Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7103-7112, June 13-19, 2020.
31 Y. O. Adu-Gyamfi, S. K. Asare, A. Sharma and T. Tienaah, "Automated vehicle recognition with deep convolutional neural networks," Transportation Research Record, vol. 2645, no. 1, pp. 113-122, 2017.   DOI
32 B. Zhang, "Reliable classification of vehicle types based on cascade classifier ensembles," IEEE Transactions on Intelligent Transportation Systems, vol. 14, no. 1, pp. 322-332, 2013.   DOI
33 M. J. Leotta and J. L. Mundy, "Vehicle surveillance with a generic, adaptive, 3D vehicle model," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 7, pp. 1457-1469, 2011.   DOI
34 X. C. Liu, W. Liu, J. K. Zheng, C. G. Yan and T. Mei, "Beyond the Parts: Learning Multi-view Cross-part Correlation for Vehicle Re-identification," in Proc. of ACM International Conference on Multimedia, pp. 907-915, October 12-16, 2020.
35 N. Baek, S. M. Park, K. J. Kim and S. B. Park, "Vehicle color classification based on the support vector machine method," in Proc. of International Conference on Intelligent Computing, pp. 1133-1139, August 21-24, 2007.
36 Q. Zhang, L. Zhuo, J. F. Li, J. Zhang, H. Zhang and X. G. Li, "Vehicle color recognition using Multiple-Layer Feature Representations of lightweight convolutional neural network," Signal Processing, vol. 147, pp. 146-153, 2018.   DOI