工程科学学报2017，Vol.39Issue(8)：1238-1243,6.DOI:10.13374/j.issn2095-9389.2017.08.014
序列图像运动自适应V1-MT光流估计算法
Bio-inspired motion-adaptive estimation algorithm of sequence image
摘要
Abstract
To overcome the insufficiencies of varying illumination, large displacement estimation, and outlier removal, a motion-adaptive V1- MT (MAV1MT) motion estimation algorithm based on machine learning and a bio-inspired model of sequence image was proposed, starting from the theory of visual cognition. First, a structure-texture decomposition technique based on the Rudin Osher Fatemi (ROF) model was introduced to manage the variation in illumination and color. Then, a pooling stage at the MT level with non-normalization, which combines the afferent V1 responses using the adaptive weights trained by ridge regression, is modeled to ob-tain the local velocities. Finally, through introducing the coarse-to-fine method and pyramid structure subsampling of the local motion, the MAV1MT model is used on realistic video. Theoretical analysis and experimental results suggest the new algorithm, which is more fitting to information processing features of the human visual system, has universal, effective and robust motion perception perform-ance.关键词
光流/V1/MT/时空滤波器/运动感知/岭回归Key words
optical flow/V1/MT/spatial-temporal filter/motion perception/ridge regression分类
信息技术与安全科学引用本文复制引用
李帅,樊晓光,许悦雷,李文倩,黄金科..序列图像运动自适应V1-MT光流估计算法[J].工程科学学报,2017,39(8):1238-1243,6.基金项目
国家自然科学基金资助项目(61372167,61379104) （61372167,61379104）
