3D ordinal constraint in spatial configuration for robust scene recognition

This paper proposes a scene recognition strategy that integrates the appearance based local SURF features and the geometry based 3D ordinal constraint. Firstly, we show that spatial ordinal ranks of 3D landmarks are well correlated across large camera viewpoint and view direction changes and thus serve as a powerful tool for scene recognition. Secondly, ordinal depth information is acquired in a simple and robust manner when the camera undergoes a bio-mimic ‘Turn-back-and-Look’ TBL) motion. Thirdly, a scene recognition strategy is proposed by combining local SURF feature matches and global 3D rank correlation coefficient into the scene recognition decision process. The performance is validated and evaluated over four indoor and outdoor databases.