基于多特征信息自适应融合的视频目标跟踪算法

针对单一视觉特征跟踪的局限性,提出一种根据场景变化动态建立目标模型的粒子滤波视觉跟踪算法,方法首先选择简单且具有互补性的色彩与纹理特征描述表示当前图像,然后在粒子滤波框架下,利用民主融合策略进行信息融合,从而提高目标观测模型的鲁棒性;分析和实验表明, 算法对视频运动目标的任意平移、转动、部分遮挡、光照变化以及相似物干扰等情况下的跟踪均具有较好的效果.

TARGET TRACKING WITH PARTICLE FILTER BASED ON MULTIPLE CUES FUSION

To overcome the shortcoming of single visual cue in complex environments, a tracking algorithm based on the multi-cue adaptive fusion is proposed. The color cue and the texture based on the discrete wavelet transform (DWT) are utilized to describe the target. Through experiments, the result of better tracking are obtained in circumstances that the target is arbitrarily moving or rotating, partially or completely occlusion, as well as the light changes. When the target with similar color appears, the tracking algorithm with the texture model can distinguish the target, thus addressing the collision problem of similar targets.