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Toward Moving Objects Detection in 3D-Lidar and Camera Data

In this paper, we present a new algorithm named IPCC for Iterative Photo Consistency Check. The goal of this one is to detect a posteriori moving object in both camera and range data. The range data may be provided by different sensor such as: Riegl, Kinect or Velodyne with no distinction. The key idea is to consider that range data acquired on static objects are photo-consistent, they have the same color and texture in all the camera images, but range data acquired on moving object are not photo-consistent. The main problem is to take in account that range finding sensor and camera are not synchronous, so what is seen in camera is not what range finding sensors acquire. This work propose an original way to estimate photo-consistency of range data by using his 3D neighborhood as a texture descriptor. A Gaussian mixture method has been developed to deal with occluded background. Moreover, we will seen how to remove non photo-consistent range data from the scene by an erosion process and how to repair images by inpainting. Finally, experiments will show the relevance of the proposed method in terms of both accuracy and computation time.