1 |
T. H. Yoo, G. S. Lee & S. H. Lee. (2012). Window Production Method based on Low-Frequency Detection for Automatic Object Extraction of GrabCut. Journal of Digital Convergence, 10(8), 211-217
DOI
|
2 |
H. H. Han, G. S. Lee, J. Y. Lee & S. H. Lee. (2012). Region Segmentation Technique Based on Active Contour for Object Segmentation, Journal of Digital Convergence, 10(3), 167-172.
DOI
|
3 |
J. C. Han, B. C. Koo & K. J. Cheoi. (2017). Obstacle Detection and Recognition System for Autonomous Driving Vehicle. Journal of Convergence for Information Technology, 7(6), 229-235. DOI : 10.22156/CS4SMB.2017.7.6.229
DOI
|
4 |
M. K. Kwon & H. S. Yang. (2017). A scene search method based on principal character identification using convolutional neural network. Journal of Convergence for Information Technology, 7(2), 31-36. DOI : 10.22156/CS4SMB.2017.7.2.031
DOI
|
5 |
A. H. Ahmed, K. Kpalma & A. O. Guedi. (2017, December). Human Detection Using HOG-SVM, Mixture of Gaussian and Background Contours Subtraction. In 2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) (pp. 334-338). IEEE.
|
6 |
B. Meus, T. Kryjak & M. Gorgon. (2017, September). Embedded vision system for pedestrian detection based on HOG+SVM and use of motion information implemented in Zynq heterogeneous device. In Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), (pp. 406-411). IEEE.
|
7 |
J. H. Kim. (2015). A Study on Tracking in Video Using Modified Particle Filter. Master dissertation. Kwangwoon University, Seoul.
|
8 |
N. Dalal & B. Triggs. (2005, June). Histograms of oriented gradients for human detection. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on (Vol. 1, pp. 886-893). IEEE.
|
9 |
C. Cortes, & V. Vapnik. (1995). Support-vector networks. Machine learning, 20(3), 273-297.
DOI
|
10 |
J. H. Baek, J. S. Kim & E. T. Kim. (2014, May). Pedestrian detection with NIR sensor-based HOG-SVM. Institude of Control, Robotics and Systems. (pp. 650-651).
|
11 |
Daimler Mono Ped. Detection Benchmark Data set. http://www.gavrila.net
|
12 |
S. K. Pyo, G. S. Lee, Y. S. Park, S. H. Lee. (2018). A license plate detection method based on contour extraction that adapts to environmental changes. Journal of the Korea Convergence Society, 9(9), 31-39.
DOI
|
13 |
H. Song, Y. Zheng & K. Zhang. (2016). Robust visual tracking via self-similarity learning. Electronics Letters, 53(1), 20-22. DOI : 10.1049/el.2016.3011
DOI
|
14 |
J. Y. Kim. (2015). Method on Detection Specific Region Using License Plate Edge Feature In Car Image. Master dissertation. Kwangwoon University, Seoul.
|
15 |
J. H. Park. (2017). Improved face detection algorithm using color distribution and shape characteristics. Master dissertation. Kwangwoon University, seoul.
|
16 |
M. Cen & C. Jung. (2017). Complex Form of Local Orientation Plane for Visual Object Tracking. IEEE Access, 5, 21597-21604. DOI : 10.1109/ACCESS.2017.2756699
DOI
|
17 |
Q. Xie, O. Remil, Y. Guo, M. Wang, M. Wei & J. Wang. (2018). Object Detection and Tracking Under Occlusion for Object-Level RGB-D Video Segmentation. IEEE Transactions on Multimedia. 20(3). 580-592. DOI : 10.1109/TMM.2017.2751965
DOI
|
18 |
L. Lan, X. Wang, S. Zhang, D. Tao, W. Gao & T. S. Huang. (2018). Interacting Tracklets for Multi-Object Tracking. IEEE Transactions on Image Processing. 27(9). 4585-4597 DOI : 10.1109/TIP.2018.2843129
DOI
|
19 |
R. Yu, I.. Cheng, B. Zhu, S. Bedmutha & A. Basu. (2018). Adaptive Resolution Optimization and Tracklet Reliability Assessment for Efficient Multi-Object Tracking. IEEE Transactions on Circuits and Systems for Video Technology. 28(7). 1623-1633. DOI : 10.1109/TCSVT.2017.2668278
DOI
|