智能系统学报2016，Vol.11Issue(1)：124-128,5.
压缩感知W-HOG特征的运动手势跟踪
Motion gesture tracking based on compressed sensing W-HOG features
史东承 1倪康1
作者信息
- 1. 长春工业大学 计算机科学与工程学院，吉林 长春130012
- 折叠
摘要
Abstract
The use of a single or simple feature for gesture tracking always induces tracking errors. To improve the accuracy of hand tracking, this study uses compressed⁃sensing motion tracking to track a hand and extracts HOG features in the movement area instead of original generalized class Harr features to track the target. At the same time, to reduce the accumulation of errors of gesture tracking generated by weight series, such as HOG features of different image blocks, the study calculates the HOG feature weight and effectively integrates the weight with HOG features to form W⁃HOG compression characteristics. The statistical experimental results show that the improved al⁃gorithm provided increased accuracy by approximately 16% compared with CT algorithm and approximately 6%compared with HOG⁃CT algorithm. Moreover, the algorithm can accurately detect the moving gesture in a complex background, improve the tracking robustness of gesture tracking in circumstances of illumination changes and back⁃ground objects with a color similar to the skin, and reduce the occurrence of gesture tracking drifting.关键词
压缩感知/Harr特征/HOG特征/手势跟踪/跟踪漂移Key words
compressed sensing/Harr features/HOG features/gesture tracking/tracking drifting分类
信息技术与安全科学引用本文复制引用
史东承,倪康..压缩感知W-HOG特征的运动手势跟踪[J].智能系统学报,2016,11(1):124-128,5.
