项目名称: 基于蛙眼视觉模型的运动目标检测、跟踪及交通场景分析方法研究
项目编号: No.91320103
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: 李智勇
作者单位: 湖南大学
项目金额: 60万元
中文摘要: 复杂场景下的运动目标检测、跟踪与分析是当前视觉计算领域基础性难点问题,研究难度大,应用前景广阔,具有重要研究意义。本课题将生物视觉认知理论、视觉信息处理方法与优化设计思想相结合,研究运动视觉计算的新方法,主要研究基于生物视觉机理的运动认知计算模型、运动目标检测与分析方法、以及复杂运动场景下的计算策略与算法。其关键思路是基于蛙眼运动视觉认知机理,研究提出新的运动视觉感知计算模型与选择性注意计算框架,建立以运动不变特征有效编码为核心的目标描述、运动检测、目标识别与跟踪分析方法,设计针对复杂视觉场景与认知计算任务的高效、鲁棒计算策略与算法,及其并行计算模式与优化方法。项目采用理论分析、仿真实验与技术验证相结合的方法,以无人驾驶车作为算法测试对象与技术验证平台,目标是为解决复杂运动视觉计算与交通场景分析探索新的思路与方法,同时也为解决更广泛意义上的视觉计算任务建立新的计算模式与范例。
中文关键词: 目标检测和跟踪;蛙眼视觉特征;多特征融合;分布场;智能优化算法
英文摘要: Moving target detection,tracking and analysis under complex scene is a fundamental and difficult problem in the field of vision computing, whose technology can be applied in many engineering domains. However, there is few general effective computing method for solving these problems nowadays. Research on the issue has important theoretical significance and practical engineering value. Integrating the biological vision cognitive theory, vision information processing methods and optimization design principle, this project studies novel motion vision computing method, which mainly focuses on the motion vision cognitive computing model, the method of motion feature detection and object analysis, as well as the strategies and algorithms of motion vision analysis under complex scene. The key ideas are as follows: according to the frog motion vision cognitive mechanism, propose a motion vision perceptive computing model and selective attention computing framework; establish the corresponding computing methods on object description, moving object detection, object recognition, object tracking and analysis cored on the effective coding of motion-invariant features; design effective robust computing strategies and algorithms for complex visual scene and computing tasks; enhance above algorithms performance by applyi
英文关键词: object detection and tracking;frog’s visual characteristics;multiple features fusion;distribution fields;intelligent optimization algorithm