c-M2DP: A Fast Point Cloud Descriptor with Color Information to Perform Loop Closure Detection

Abstract

We present c-M2DP, a fast global point cloud descriptor that combines color and shape information, and perform loop closure detection using it. Our approach extends the M2DP descriptor by incorporating color information. Along with M2DP shape signatures, we compute color signatures from multiple 2D projections of a point cloud. Then, a compact descriptor is computed by using SVD to reduce its dimensionality. We performed experiments on public available datasets using both camera-LIDAR fusion and stereo depth estimation. Our results show an overall accuracy improvement over M2DP while maintaining efficiency, and are competitive in comparison with another color and shape descriptor.