Tailored carrier/bacteria technology for rehabilitation of areas with pesticide-containing pollution – AQUAREHAB WP2

Postprint (published version

Dynamic texture detection, segmentation and analysis

Dynamic textures are common in natural scenes. Examples of dynamic textures in video include fire, smoke, clouds, trees in the wind, sky, sea and ocean waves etc. In this showcase, (i) we develop real-time dynamic texture detection methods in video and (ii) present solutions to video object classification based on motion information

Robust motion segmentation with unknown correspondences

Part IVMotion segmentation can be addressed as a subspace clustering problem, assuming that the trajectories of interest points are known. However, establishing point correspondences is in itself a challenging task. Most existing approaches tackle the correspondence estimation and motion segmentation problems separately. In this paper, we introduce an approach to performing motion segmentation without any prior knowledge of point correspondences. We formulate this problem in terms of Partial Permutation Matrices (PPMs) and aim to match feature descriptors while simultaneously encouraging point trajectories to satisfy subspace constraints. This lets us handle outliers in both point locations and feature appearance. The resulting optimization problem can be solved via the Alternating Direction Method of Multipliers (ADMM), where each subproblem has an efficient solution. Our experimental evaluation on synthetic and real sequences clearly evidences the benefits of our formulation over the traditional sequential approach that first estimates correspondences and then performs motion segmentation.Pan Ji, Hongdong Li, Mathieu Salzmann, and Yuchao Da