Segment Tracking via a Spatiotemporal Linking Process including Feedback Stabilization in an n-D Lattice ModelReportar como inadecuado




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1

Bernstein Center for Computational Neuroscience Göttingen, Max-Planck Institute for Dynamics and Self-Organization, Bunsenstrasse 10, 37073 Göttingen, Germany

2

Institut de Robòtica i Informàtica Industrial CSIC-UPC, Llorens i Artigas 4-6, 08028 Barcelona, Spain

3

Bernstein Center for Computational Neuroscience Göttingen, Department for Computational Neuroscience, III. Physikalisches Institut, Georg-August University Göttingen - Biophysik, Friedrich-Hund Platz 1, 37077 Göttingen, Germany;





*

Author to whom correspondence should be addressed.



Abstract Model-free tracking is important for solving tasks such as moving-object tracking and action recognition in cases where no prior object knowledge is available. For this purpose, we extend the concept of spatially synchronous dynamics in spin-lattice models to the spatiotemporal domain to track segments within an image sequence. The method is related to synchronization processes in neural networks and based on superparamagnetic clustering of data. Spin interactions result in the formation of clusters of correlated spins, providing an automatic labeling of corresponding image regions. The algorithm obeys detailed balance. This is an important property as it allows for consistent spin-transfer across subsequent frames, which can be used for segment tracking. Therefore, in the tracking process the correct equilibrium will always be found, which is an important advance as compared with other more heuristic tracking procedures. In the case of long image sequences, i.e., movies, the algorithm is augmented with a feedback mechanism, further stabilizing segment tracking. View Full-Text

Keywords: model-free segment tracking; image motion; image segmentation model-free segment tracking; image motion; image segmentation





Autor: Babette Dellen 1,2,* , Eren Erdal Aksoy 3 and Florentin Wörgötter 3

Fuente: http://mdpi.com/



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