1 |
T. Vojir, "Tracking Dataset," 2017 [Online]. Available: http://cmp.felk.cvut.cz/-vojirtom/dataset/.
|
2 |
M. Kristan, A. Leonardis, J. Matas, M. Felsberg, R. Pflugfelder, L. Cehovin Zajc, et al., "The sixth visual object tracking vot2018 challenge results," in Proceedings of the 14th European Conference on Computer Vision (ECCV), Munich, Germany, 2018, pp. 3-53.
|
3 |
L. Leal-Taixe, A. Milan, I. Reid, S. Roth, and K. Schindler, "Motchallenge 2015: towards a benchmark for multi-target tracking," 2015 [Online]. Available: https://arxiv.org/abs/1504.01942.
|
4 |
C. Sutheerakul, N. Kronprasert, M. Kaewmoracharoen, and P. Pichayapan, "Application of unmanned aerial vehicles to pedestrian traffic monitoring and management for shopping streets," Transportation Research Procedia, vol. 25, pp. 1717-1734, 2017.
DOI
|
5 |
K. V. Sriram and R. H. Havaldar, "Human detection and tracking in video surveillance system," in Proceedings of 2016 IEEE International Conference on Computational Intelligence and Computing Research, Chennai, India, 2016, pp. 1-3.
|
6 |
F. Li, R. Zhang, and F. You, "Fast pedestrian detection and dynamic tracking for intelligent vehicles within V2V cooperative environment," IET Image Processing, vol. 11, no. 10, pp. 833-840, 2017.
DOI
|
7 |
A. W. M. Smeulders, D. M. Chu, R. Cucchiara, S. Calderara, A. Dehghan, and M. Shah, "Visual tracking: an experimental survey," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 7, pp. 1442-1468, 2014.
DOI
|
8 |
A. Yilmaz, O. Javed, and M. Shah, "Object tracking: a survey," ACM Computing Survey, vol. 38, no. 4, article no. 13, 2006.
|
9 |
J. Zhu, H. Yang, N. Liu, M. Kim, W. Zhang, and M. H. Yang, "Online multi-object tracking with dual matching attention networks," in Computer Vision - ECCV 2018. Cham: Springer, 2018, pp. 366-382.
|
10 |
A. Dehghan, H. Idrees, A. R. Zamir, and M. Shah, "Automatic detection and tracking of pedestrians in videos with various crowd densities," in Pedestrian and Evacuation Dynamics 2012. Cham: Springer, 2014, pp. 3-19.
|
11 |
Y. Jiang, H. Shin, J. Ju, and H. Ko, "Online pedestrian tracking with multi-stage re-identification," in Proceedings of 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, Lecce, Italy, 2017, pp. 1-6.
|
12 |
K. He, X. Zhang, S. Ren, and J. Sun, "Deep residual learning for image recognition," in Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, 2016, pp. 770-778.
|
13 |
N. Yu, Z. Yu, F. Gu, T. Li, X. Tian, and Y. Pan, "Deep learning in genomic and medical image data analysis: challenges and approaches," Journal of Information Processing Systems, vol. 13, no. 2, pp. 204-214, 2017.
DOI
|
14 |
X. Feng, "Infrared and visible image fusion based on NSCT and deep learning," Journal of Information Processing Systems, vol. 14, no. 6, pp. 1405-1419, 2018.
DOI
|
15 |
Z. Jiang, S. Gao, and W. Dai, "A CTR prediction approach for text advertising based on the SAE-LR deep neural network," Journal of Information Processing Systems, vol. 13, no. 5, pp. 1052-1070, 2017.
DOI
|
16 |
S. D. You, C. Liu, and W. Chen, "Comparative study of singing voice detection based on deep neural networks and ensemble learning," Human-centric Computing and Information Sciences, vol. 8, no. 1, article no. 34, 2018.
|
17 |
S. Ren, K. He, R. B. Girshick, and J. Sun, "Faster R-CNN: towards real-time object detection with region proposal networks," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 6, pp. 1137-1149, 2017.
DOI
|
18 |
J. Huang, V. Rathod, C. Sun, M. Zhu, A. Korattikara, A. Fathi, et al., "Speed/accuracy trade-offs for modern convolutional object detectors," in Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, 2017, pp. 3296-3297.
|
19 |
E. Bochinski, V. Eiselein, and T. Sikora, "High-speed tracking-by-detection without using image information," in Proceedings of 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, Lecce, Italy, 2017, pp. 1-6.
|
20 |
M. T. N. Truong and S. Kim, "Parallel implementation of color-based particle filter for object tracking in embedded systems," Human-centric Computing and Information Sciences, vol. 7, article no. 2, 2017.
|