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中文摘要：
为了解决非刚体目标跟踪过程中由目标形状快速变化带来的困难,提出了利用SIFT特征联合匹配的非刚体目标跟踪算法。首先分别提取目标模板和当前搜索区域的SIFT特征点;然后利用改进的联合匹配策略在目标模板和当前搜索区域之间进行特征匹配;最后根据匹配结果确定目标在当前帧的位置和尺度。改进的联合匹配策略在构建相似度矩阵时,不但利用了具有旋转和尺度不变性的SIFT特征向量,并且充分考虑了特征点的空间位置信息,有效提高了特征匹配的准确性。将这种改进的联合匹配策略成功地引入到SIFT匹配跟踪中,克服了传统SIFT匹配算法用于非刚体目标跟踪时的缺陷。实验结果表明,该算法对目标的非刚性形变、尺度变化以及背景干扰都具有较强的鲁棒性。
英文摘要：
To solve the problems in non-rigid object tracking, such as the significant and rapid variation in shape as well as appearance, an efficient tracking algorithm based on joint matching of SIFT features is proposed in this paper. Firstly, local SIFT key points of the object template and the current searching area are detected and described. Then, the key points are matched via the improved joint matching strategy, and the right matching pairs are picked out. Finally, the object＇s location and size are calculated according to the matching results. When constructing the similarity matrix, the improved joint matching strategy exploits the rotation and scale invariance of SIFT features, and considers the spatial information of the key points, which effectively en- hances the feature matching accuracy. This paper successfully introduces the improved matching strategy to the SIFT matching tracking, which overcomes the defect of the traditional SIFT matching algorithm in non-rigid ob- ject tracking. The experimental results indicate that the proposed algorithm is robust to object＇s non-rigid deformation, scale change and background distraction.
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