Object-Based Spatial Segmentation of Video Guided by Depth and Motion Information

Abstract

Automatic spatial video segmentation is a problem without a general solution at the current state-of-the-art. Most of the difficulties arise from the process of capturing images, which remain a very limited sample of the scene they represent. The capture of additional information, in the form of depth data, is a step forward to address this problem. We start by investigating the use of depth data for better image segmentation; a novel segmentation framework is proposed, with depth being mainly used to guide a segmentation algorithm on the colour information. Then, we extend the method to also incorporate motion information in the segmentation process. The effectiveness and simplicity of the proposed method is documented with results on a selected set of images sequences. The achieved quality raises the expectation for a significant improvement on operations relying on spatial video segmentation as a pre-process.