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학술지
RGB-D 이미지에서 인체 영역 검출을 위한 프레임워크
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- 발행일
- 201612
- 출처
- 멀티미디어학회논문지, v.19 no.12, pp.1927-1935
- ISSN
- 1229-7771
- 출판사
- 한국멀티미디어학회
- 협약과제
- 16CS1900, 청소년용 실감 체험형 스포츠 통합플랫폼 기술 개발, 김명규
- 초록
- This paper propose a framework for human body parts in RGB-D image. We conduct tasks of obtaining person area, finding candidate areas and local detection in order to detect hand, foot and head which have features of long accumulative geodesic distance. A person area is obtained with background subtraction and noise removal by using depth image which is robust to illumination change. Finding candidate areas performs construction of graph model which allows us to measure accumulative geodesic distance for the candidates. Instead of raw depth map, our approach constructs graph model with segmented regions by quadtree structure to improve searching time for the candidates. Local detection uses HOG based SVM for each parts, and head is detected for the first time. To minimize false detections for hand and foot parts, the candidates are classified with upper or lower body using the head position and properties of geodesic distance. Then, detect hand and foot with the local detectors. We evaluate our algorithm with datasets collected Kinect v2 sensor, and our approach shows good performance for head, hand and foot detection.
- KSP 제안 키워드
- Background subtraction(BS), Body parts, Depth Map, Depth image, False detection, Foot Detection, Geodesic distance, Graph model, Head position, Human body, Illumination change