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	CPRM: Color perception and representation model for fabric image based on color sensitivity of human visual system 期刊论文 OAI收割 TEXTILE RESEARCH JOURNAL, 2023, 页码: 15 作者: Zhao, Xueqing; Yang, Han; Shi, Xin; Liu, Kaixuan; Wang, Yun \| 收藏 \| 浏览/下载：27/0 \| 提交时间：2023/03/20 Color perception color representation fabric image color sensitive function visual computational model color contrast
	Modeling of Visual Cognition, Body Sense, Motor Control and Their Integrations 期刊论文 OAI收割 Systems Science & Control Engineering, 2017, 卷号: -, 期号: Issue, 页码: - 作者: Qiao H(乔红); L. Hu \| 收藏 \| 浏览/下载：33/0 \| 提交时间：2018/01/04 Computational Modeling Biological Mechanism Visual Cortex Pain Prediction Bio-inspired Model Machine Learning Neural Networks
	Editorial: Modeling of Visual Cognition, Body Sense, Motor Control and Their Integrations 期刊论文 OAI收割 FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2016, 卷号: 10 作者: Qiao, Hong; Hu, Li 收藏 \| 浏览/下载：50/0 \| 提交时间：2017/02/14 computational modeling biological mechanism visual cortex pain prediction bio-inspired model machine learning neural networks
	Editorial: Modeling of Visual Cognition, Body Sense, Motor Control and Their Integrations 期刊论文 OAI收割 FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2016, 卷号: 10, 期号: 0, 页码: 1-3 作者: Qiao, Hong; Hu, Li 收藏 \| 浏览/下载：57/0 \| 提交时间：2017/02/13 computational modeling biological mechanism visual cortex pain prediction bio-inspired model machine learning neural networks
	Computational Primitives of Visual Perception", Proceeding of the International Conference on Image Processing 会议论文 OAI收割 Cairo, Egypt, 2009 作者: Yongzhen Huang; Kaiqi Huang; Tieniu Tan \| 收藏 \| 浏览/下载：21/0 \| 提交时间：2016/12/30 Computational Model descriptor visual Perception
	Real time tracking by LOPF algorithm with mixture model (EI CONFERENCE) 会议论文 OAI收割 MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, November 15, 2007 - November 17, 2007, Wuhan, China Meng B.; Zhu M.; Han G.; Wu Z. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently we first use Sobel algorithm to extract the profile of the object. Then we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.