상세정보
학술지
A Novel Real Time Video Tracking Framework using Adaptive Discrete Swarm Optimization
- 저자
- 배창석, 강규창, Guang Liu, Yuk Ying Chung
- 발행일
- 201612
- 출처
- Expert Systems with Applications, v.64, pp.385-399
- ISSN
- 0957-4174
- 출판사
- Elsevier
- 협약과제
- 16MS2400, (1세부) 실시간 대규모 영상 데이터 이해·예측을 위한 고성능 비주얼 디스커버리 플랫폼 개발, 박경
- 초록
- This paper has proposed a new adaptive discrete swarm optimization (ADSO) for the video tracking framework. Each target object is first presented by a search window with four-dimensional features, which include 2D coordinates of the search window, its width and height. The image in the search window of a target object is extracted to calculate the HSV histograms, which are used to establish a feature model for the target object. Then the particles fly in a sub-search-space to find an optimal match of the target. If any occlusion or disappearance of the target object is detected, the particles will adaptively update their searching strategies in order to recapture the target. The experimental results demonstrate that the ADSO can out-perform the traditional PSO algorithm in the aspects of high accuracy rate and fast tracking and relocating speed.
- KSP 제안 키워드
- Accuracy Rate, Feature model, Four-dimensional, High accuracy, Optimal match, PSO algorithm, Real-time video, Search Window, dimensional features, fast tracking, swarm optimization