SIFT와 다중측면히스토그램을 이용한 다중물체추적 = Multiple Object Tracking Using SIFT and Multi-Lateral Histogram

다국어 초록 (Multilingual Abstract)

In multiple object tracking, accurate detection for each of objects that appear sequentially and effective tracking in complicated cases that they are overlapped with each other are very important. In this paper, we propose a multiple object tracking system that has a concrete detection and tracking characteristics by using multi-lateral histogram and SIFT feature extraction algorithm. Especially, by limiting the matching area to object's inside and by utilizing the location informations in the keypoint matching process of SIFT algorithm, we advanced the tracking performance for multiple objects. Based on the experimental results, we found that the proposed tracking system has a robust tracking operation in the complicated environments that multiple objects are frequently overlapped in various of directions.

참고문헌 (Reference)

1 김신홍, "고속의 홍채인식을 위한 USN기반의 임베디드 시스템 구현" 대한임베디드공학회 4 (4): 190-194, 2009

2 H. Bay, "SURF : Speeded Up Robust Features" 404-417, 2006

3 D. G. Lowe, "Object Recognition form Local Scale-Invariant Features" 1150-1157, 1999

4 H. Zhang, "Object Detection using Spatial Histogram features" 24 (24): 327-341, 2006

5 E. R. Davis, "Lateral histogram for efficient object location : Speed versus ambiguity" 6 (6): 189-198, 1987

6 Q. Jin, "Iris Recognition by New Invariant Feature nDescriptor" 9 (9): 1943-1948, 2013

7 E. Rafajlowicz, "Improving the Efficiency of Computing Defects by Learning RBF Nets with MAD Loss" 146-153, 2008

8 Ecole Polytechnique, "Computer Vision Laboratory"

9 K. Mikolajczyk, "A Performance Evaluation of Local Descriptors" 27 (27): 1615-1630, 2005