项目名称: 基于视觉皮层信息处理机制的行人检测与行为识别
项目编号: No.91320102
项目类型: 重大研究计划
立项/批准年度: 2014
项目学科: 自动化学科
项目作者: 刘海华
作者单位: 中南民族大学
项目金额: 70万元
中文摘要: 视觉感知作为环境分析和理解的主要手段之一,在复杂交通环境下的行人检测与行为识别中发挥重要作用,是无人驾驶技术中备受关注的研究内容。目前虽已取得许多成果,但普遍缺乏鲁棒性。为此本项目拟模拟视觉皮层信息处理机制,根据视觉感知、视觉注意、视觉信息加工机理,构建行人检测与行为识别系统。以视皮层细胞动态属性为基础,建立能检测时空信息的感知计算模型,提出模拟视皮层环绕抑制作用的时空信息稀疏处理方法,保证信息感知的有效性;根据视觉皮层环绕抑制和易化的相互作用理论,提出新的视觉注意计算模型,给出行人对象检测方法;依据脉冲神经元计算模型,研究神经元膜电位的自动阈值方法,分析神经元的脉冲链,提出基于神经元平均发放率的特征提取方法。在此基础上,研究这些理论的并行计算方法,建立行人检测与行为识别实时系统,通过车载实验,验证新理论和新方法。本项目的研究可以实现准确的行人检测与识别,推动无人驾驶技术的发展。
中文关键词: 行为识别;行人检测;特征提取;脉冲神经元;脉冲神经网络
英文摘要: As one of the main means of the environmental analysis and understanding for driverless vehicle, visual perception plays an important role in pedestrian detection, action recognition etc., and becomes one of the hot topics in the research field. Up to now, although a lot of achievements have been made, they are generally lack of robustness. To this end, the project intends to establish a bio-inspired system for pedestrian detection and action recognition in road traffic, which simulates neural mechanisms of the dorsal stream in the visual cortex based on the theory of visual perception, visual attention and visual information processing. Firstly, visual perception computational model is built for effective detection of spatiotemporal information from videos based on dynamic properties of cells in visual cortex. The sparse coding for spatiotemporal information is introduced into the model with center surround suppression. Secondly, a new visual attention computational model is proposed by using the theories of surround inhibition and facilitation in visual cortex, and the method of pedestrian detection is proposed afterwards. Finally, based on the integrate-fire model of spiking neurons, an automatic threshold method for membrane potential of neurons is proposed through statistical analysis of the responses of al
英文关键词: action recognition;pedestrain detection;feature extraction;spiking neuron;spiking neural networks