Graph Signal Processing for Scene Representation and Analysis

Graph signal processing (GSP) is an emerging field that provides a new family of tools for analyzing signals that could be modeled on vertices connected by edges. In this paper, we describe two examples of how GSP is being applied for scene representation and analysis, where the scene is either captured as video sequences or point clouds. In the first example, we show that novel graph constructions can be used to robustly segment moving foreground objects from the background of video sequences with ego-motions. In the second example, we employ a graph-based transform to efficiently code attributes associated with the point clouds. We demonstrate with the two examples the potential benefits of using GSP tools for scene representation and analysis.