A ground truth for motion-based video-object segmentation

This paper describes the design procedure followed to generate a ground truth for the evaluation of motion-based algorithms for video-object segmentation. A thorough review and classification of the critical factors that affect the behavior of segmentation algorithms results in a set of video scripts which have then been filmed. Foreground objects have been recorded in a chroma studio, in order to automatically obtain pixel-level high quality segmentation masks for each generated sequence. The resulting corpus (segmentation ground-.truth plus filmed sequences mounted over different backgrounds) is available for research purposes under a license agreement.