For the large computation and the real-time tracking to be hard to achieve by traditional fragment based tracking algorithm, an improved fragment based algorithm was proposed. Firstly, in order to reduce the negative effect yielded by the background noise, the region of the tracked object was divided into more fragments. Then, the position and the range of the search region were identified according to the movement information of the object. By utilizing a fast hierarchical adaptive search approach which adopts different search patterns in different steps, most of the calculations for invalid positions were skipped, and the coordinate where the candidate was most similar with the object template was obtained quickly. Moreover, the improved algorithm was implemented and optimized on a DSP. Experimental results indicate that the improved algorithm can process the image of 768 pixel×576 pixel on DM642 at a processing speed of 30 frame/s. Compared with the traditional fragment based tracking algorithm, it shows a more precise tracking and saves the processing time about 47. 5％. These results show that the improved algorithm overcome the shortcomes from traditional fragment based tracking algorithms, and can achieve a real-time tracking with better tracking performance.%针对传统的分块跟踪算法计算量大,难以实时地对运动目标进行跟踪这一问题,提出了一种改进的分块跟踪算法.首先,为降低背景噪声对跟踪性能产生的不利影响,提出的算法对目标所在矩形窗口进行了更细致的划分;然后,根据目标运动信息确定搜索范围和搜索中心,采用分层次的自适应搜索算法,在每一层采用不同的搜索策略逐步逼近与目标模板最相似的位置,避免算法将时间过多地浪费在无效位置的运算上;最后,给出了改进算法在DSP上的实现和优化方法.实验结果显示,该改进算法能够在DM642上以30 frame/s的速度处理768 pixel×576 pixel的图像,与传统的分块跟踪算法相比,提高了跟踪精度,运算时间减小了约47.5%.该改进算法较好地解决了传统分块算法的缺陷,实现了在嵌入式系统上对运动目标的实时跟踪.
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