http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Graph-based Object Detection and Tracking in H.264/AVC bitstream for Surveillance Video
호와리(Houari Sabirin),김문철(Kim Munchurl) 한국방송·미디어공학회 2010 한국방송공학회 학술발표대회 논문집 Vol.2010 No.11
In this paper we propose a method of detecting moving object in H.264/AVC bitstream by representing the 4x4 block partition units as nodes of graph. By constructing hierarchical graph by taking into account the relation between nodes and the spatial-temporal relations between graphs in frames, we are able to track small objects, distinguish two occluded objects, and identify objects that move and stop alternatively.
Houari Sabirin(호와리),Munchurl Kim(김문철) 한국방송·미디어공학회 2012 한국방송공학회 학술발표대회 논문집 Vol.2012 No.7
This paper presents a graph-based method of detecting and tracking moving objects in H.264/SVC bitstreams for video surveillance applications that makes use the information from spatial base and enhancement layers of the bitstreams. In the base layer, segmentation of real moving objects are first performed using a spatio-temporal graph by removing false detected objects via graph pruning and graph projection, followed by graph matching to precisely identify the real moving objects over time even under occlusion. For the accurate detection and reliable tracking of moving objects in the enhancement layer, as well as saving computational complexity, the identified block groups of the real moving objects in the base layer are then mapped to the enhancement layer to provide accurate and efficient object detection and tracking in the bitstreams of higher resolution. Experimental results show the proposed method can produce reliable results with low computational complexity in both spatial layers of H.264/SVC test bitstreams.