项目名称: 复杂运动轨迹的不变量语义表示方法研究及应用
项目编号: No.61305020
项目类型: 青年科学基金项目
立项/批准年度: 2014
项目学科: 自动化技术、计算机技术
项目作者: 杨剑宇
作者单位: 苏州大学
项目金额: 25万元
中文摘要: 复杂运动轨迹的高效表示方法是复杂运动分析的前提和基础,也是机器视觉领域的重要问题之一。复杂运动分析在安防监控等方面有广泛的应用,对公共安全具有重要意义。本项目研究复杂运动轨迹在多个层次的运动特征分析和不变量语义表示方法。针对复杂运动的空间特征和运动学特征在运动轨迹的轨迹点层面、原子层面和高级语义层面的分布特点和变化关系,拟通过参数的不变量分析,揭示不同层面的运动特征参数对运动的语义特征的反映规律,建立复杂运动轨迹在不同层次的一般化模型和高级语义表示方法,并依此设计实时运动分析算法。研究内容包括:复杂运动轨迹不变量特征提取;低级语义划分与原子模型设计;高级语义结构分析与表示以及在运动分析中的实时性应用。本项目旨在充分挖掘复杂运动轨迹的各方面特征,提出一整套复杂运动轨迹的特征分析与高级语义表示以及实时运动识别与感知的方法,为实际工程应用提供理论和技术支持。
中文关键词: 运动轨迹;语义表示;不变量;行为识别;行为感知
英文摘要: Effective representation of complex motion trajectory is not only the basis and premise of complex motion analysis, but also one of the important problems in the research area of machine vision. Complex motion analysis is widely applied in surveillance and has important significance in public security. This project will analyze the motion features of complex motion trajectory in multiple hierarchies, and research their invariant semantic representation. Towards the spatial feature distribution and kinematic feature variation of the complex motion trajectory in point level, atom level and semantic level, base on the analysis of parameter invariants, reveal hierarchical motion characteristic parameters to reflect the regularity of motion semantic features, construct the general model and high level semantic representation of complex motion trajectory in different level, and design the real time motion analysis algorithms accordingly. The research contents include: extraction of the invariant features of complex motion trajectory, semantic segmentation in low level and atom model designation, semantic structure analysis and representation in high level, and the real time application of motion analysis. This project aims to excavate the detail features of complex motion trajectory in all aspects, present a complete
英文关键词: motion trajectory;semantic representation;invariant;action recognition;action percention