CAJ | 학술논문

针对前景和背景深度交叠或相机运动时基于深度统计的传统视频分割算法中存在的问题，提出一种基于时空测地线的方法，并证明该方法适合基于深度的视频分割。首先使用基于运动检测的方式进行初始化；然后使用基于特征点选择方式定义种子结点，特征点匹配方式构建时域链接，空间上8邻域像素连接形成空域链接，在连续两帧之间构建时空测地线传播图；最后在时空测地线传播图上使用泛化测地线距离变换将前一帧的分割结果传播到当前帧，并自适应地在传播和检测间切换消除累计误差。实验结果表明，该方法能够在复杂场景和相机运动情形下输出稳定的分割结果。
침대전경화배경심도교첩혹상궤운동시기우심도통계적전통시빈분할산법중존재적문제，제출일충기우시공측지선적방법，병증명해방법괄합기우심도적시빈분할。수선사용기우운동검측적방식진행초시화；연후사용기우특정점선택방식정의충자결점，특정점필배방식구건시역련접，공간상8린역상소련접형성공역련접，재련속량정지간구건시공측지선전파도；최후재시공측지선전파도상사용범화측지선거리변환장전일정적분할결과전파도당전정，병자괄응지재전파화검측간절환소제루계오차。실험결과표명，해방법능구재복잡장경화상궤운동정형하수출은정적분할결과。
Traditional video segmentation methods based on depth statistics often fail in case of moving camera or overlap between depth ranges of foreground and background. In this paper we propose a geo-desic-based method that is suitable for RGB-D video segmentation. The segmentation process is initialized by motion detection, then for each two consecutive frames, a geodesic spatio-temporal graph is constructed, with seed nodes selected based on image feature detection, temporal links built via feature matching and the 8 spatial neighborhoods of pixels used as spatial links. The segmentation result of previous frame then is propagated to the current frame via geodesic spatio-temporal propagation, which is conducted efficiently by generalized geodesic distance transform. Accumulated errors are eliminated by alternatively launching the process of propagation and motion detection. Experiments demonstrate the robust segmentation results for videos of complex scenes and moving camera.