BROWSE
Detail
Journal Article
RGB-D 이미지에서 인체 영역 검출을 위한 프레임워크
Cited - time in 
Share 
Share
- Issue Date
- 2016-12
- Citation
- 멀티미디어학회논문지, v.19, no.12, pp.1927-1935
- ISSN
- 1229-7771
- Publisher
- 한국멀티미디어학회
- Language
- Korean
- Type
- Journal Article
- Abstract
- 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 Keywords
- Background Subtraction, Body parts, Depth Map, Depth image, False detection, Foot Detection, Geodesic distances, Head position, Human Body, Kinect v2 sensor, Local detection