Planar surfaces detection on depth map using patch based approach

This paper proposes an unsupervised technique for detecting planar surfaces on single depth map image. The proposed method can detect planar surfaces by adopting dynamic seed growing technique without using texture information. So aided with this mechanism to control the growing process, each seed patch can grow to its maximum extent and then the next seed patch begins to grow. This process avoids over-segmentation of the whole scene. Moreover, it allows detecting semi-planer surfaces. Compared with one popular planar surface detection algorithms, i.e., RANdom SAmples Consensus(RANSAC), the accuracy of the proposed method is superior on typical indoor scenes. The proposed method can have huge technical potential for image/video segmentation and coding, enhancing the depth information of time-of-flight cameras, and finally it could be used for navigation system for humanoid robotics.