膝前區 的英文怎麼說
中文拼音 [xīqiánqū]
膝前區
英文
anterior region of knee-
Visual analysis of human motion has been receiving increasing attention from researchers in the fields of image processing and computer vision during the past few years. it has a lot of applications in virtual reality, smart surveillance system, advanced user interface, motion analysis and video compressing, etc. this paper focuses on the technology of human motion tracking based on video, first, we make a summarization of the domestic and overseas status of the research in this field. on the basis of this, we analyse the technical difficulties of human motion tracking. as most of the existing model - based methods of human motion tracking perform not so good in some situation as they need mannual intervention, and also the precision of tracking is not so satisfying during the research of tracking of walking people because of the self - occlusion of legs, this paper proposes an algorithm of automatic detection and tracking of legs of the walking people based on monocular image sequences, in which we analyse the features of walking people, track the five joints of lower limbs, get various parameters, and then re - construct the walking process. the main research achievement is as follows : 1 ) we propose an algorithm of markerless automatic extraction of leg skeleton. first we divide the video into continuous image sequences, after background subtraction, the satisfying human region could be extracted, then we get a single - connected region by converting the rgb image to binary image and median filtering. afterwards, the contour of lower limbs in the frame with a widest boundingbox is detected, using sobel operator, to find the ankle joint of leg behind according to the features and rules of walking, then, the joint of knee of leg behind, hip, ankle of leg in front, knee of leg in front could be got in turn. so, model of leg skeleton is constructed
首先將視頻分解成許多連續的靜態圖像幀，經過背景去除，把感興趣的人體區域提取出來，通過二值化，中值濾波等預處理方法得到只有人體的一個單連通區域，然後用sobel運算元檢測出boundingbox最寬幀中人體下半身的輪廓，根據運動規律及特徵找到後腿踝關節點，結合從boundingbox最窄幀中所獲取的腿長依次得到後腿膝關節，跨部關節，前腿踝關節，前腿膝關節四點，從而構建出腿部骨架模型。 2 ）實現了人體步行腿部骨架的跟蹤演算法。在完成對腿部骨架模型的自動初始化之後，本文對跨關節、膝關節及踝關節分別採用運動建模、圓周相交定點演算法、運動預測及預測點周圍搜索rgb相似矩形塊三種方法確定每一幀中其實際坐標，從而重構出腿部骨架的運動過程。
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