CAJ | 학술논문

在智能监控系统中，视频运动目标检测是目标分类和行为理解的基础。由于视频背景的复杂性，考虑检测问题中能量函数的全局优化，提出了基于典型相关的树加权置信传播（ TRW）算法用于视频运动目标检测。算法首先将视频图像分成一些图像块，构造有环图模型；然后运用TRW算法将环路分解成生成树的形式，实现有环图模型上的视频运动目标优化检测。仿真结果表明，算法具有较高的准确度，与传统的置信传播（ BP）算法相比较，能有效降低迭代次数，提高计算效率。
재지능감공계통중，시빈운동목표검측시목표분류화행위리해적기출。유우시빈배경적복잡성，고필검측문제중능량함수적전국우화，제출료기우전형상관적수가권치신전파（ TRW）산법용우시빈운동목표검측。산법수선장시빈도상분성일사도상괴，구조유배도모형；연후운용TRW산법장배로분해성생성수적형식，실현유배도모형상적시빈운동목표우화검측。방진결과표명，산법구유교고적준학도，여전통적치신전파（ BP）산법상비교，능유효강저질대차수，제고계산효솔。
Video moving object detection is the foundation of the behavior understanding and target classification in the intelligent surveillance system .As the complexity of video background , consider the global optimization of the energy function in object detection .In this paper , tree re-weighted belief propagation ( TRW) algorithm based on canonical correlation is proposed to detect the video moving objects . This algorithm firstly separates the video image into some blocks and constructs a loop model .Then it uses the TRW algorithm to decompose the loop into spanning tree and achieve the detection of the video moving objects on the loop model .The experimental results verify the veracity of the algorithm , compared with the traditional belief propagation ( BP ) algorithm, TRW can decrease the message iterations effectively and improve the computational efficiency of the algorithm.