面向增强视频的基于结构和运动恢复的摄像机定标  

Camera Tracking Based on Structure and Motion Recovery for Augmented Video

作　　者：章国锋[1] 秦学英[1] 董子龙[1] 华炜[1] 鲍虎军[1] 

机构地区：[1]浙江大学CAD&CG国家重点实验室,杭州310027

出　　处：《计算机学报》2006年第12期2104-2111,共8页Chinese Journal of Computers

基　　金：国家"九七三"重点基础研究发展规划项目基金(2002CB312104);国家创新群体科学基金(60021201);教育部博士点基金(20030335083);国家自然科学基金(60373035)资助~~

摘　　要：提出了一种高效鲁棒的长序列摄像机定标算法,能稳定处理焦距未知且变化的视频序列,适用于增强视频的应用.该算法从长视频序列中根据特征匹配点提炼出相互之间具有较长基线的关键帧,以保证求解的稳定性.算法先在关键帧序列上渐进式求解,以准确恢复特征匹配点的三维结构信息;利用精确恢复的三维点,求解整个序列的摄像机运动参数.该算法选择最适合初始化的三帧求解,并将解及时从射影空间转换到欧氏空间.实验结果显示了所恢复的摄像机参数和三维点的高度精确性,证明了该方法稳定高效,能够满足增强视频的高端要求.Robust camera tracking plays a key role in augmented video. This paper proposes an efficient and robust approach to structure and motion recovery for long video sequences with varying and unknown focal length. In this approach, a long sequence is abstracted as a sequence of key frames in-between which have long baselines in order to assure the preciseness of the solution. The sequence of the key frames are resolved incrementally in order to recover the structure of 3D points, by which the camera motion of all frames of the sequence is retrieved. The algorithm begins with three key frames suitable for initializing the sequential structure and motion computation, and the projective structure is upgraded to metric one in time though self-calibration. The implemented examples demonstrate very precise structure and motion recovery, and prove the efficiency and robustness of the proposed method.

关 键 词：增强视频 摄像机定标 自定标 欧氏重建 结构与运动恢复 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]