Motion Segmentation with Weak Labeling Priors

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8753)


Motions of organs or extremities are important features for clinical diagnosis. However, tracking and segmentation of complex, quickly changing motion patterns is challenging, certainly in the presence of occlusions. Neither state-of-the-art tracking nor motion segmentation approaches are able to deal with such cases. Thus far, motion capture systems or the like were needed which are complicated to handle and which impact on the movements. We propose a solution based on a single video camera, that is not only far less intrusive, but also a lot cheaper. The limitation of tracking and motion segmentation are overcome by a new approach to integrate prior knowledge in the form of weak labeling into motion segmentation. Using the example of Cerebral Palsy detection, we segment motion patterns of infants into the different body parts by analyzing body movements. Our experimental results show that our approach outperforms current motion segmentation and tracking approaches.


Cerebral Palsy Body Part Optical Flow Spectral Cluster Motion Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Engineering CyberneticsNTNUTrondheimNorway
  2. 2.Computer Vision LabETHZurichSwitzerland
  3. 3.Clinic for Clinical ServicesSt. Olavs University HospitalTrondheimNorway
  4. 4.Department of Laboratory Medicine, Children and Woman’s Health, Faculty of MedicineNTNUTrondheimNorway

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