Video object segmentation and tracking in stereo sequences using adaptable neural networks

نویسندگان

  • Nikolaos D. Doulamis
  • Anastasios D. Doulamis
چکیده

SEQUENCES USING ADAPTABLE NEURAL NETWORKS Nikolaos Doulamis and Anastasios Doulamis National Technical University of Athens, Electrical and Computer Engineering Department, 15773, Athens, Greece E-mail: [email protected] Abstract In this paper, an adaptive neural network architecture is proposed for efficient video object segmentation and tracking of stereoscopic sequences. The scheme includes (a) a retraining algorithm for adapting network weights to current conditions, (b) a semantically meaningful object extraction module for creating a retraining set and (c) a decision mechanism, which detects the time instances that a new network retraining is required. The retraining algorithm optimally adapts network weights by exploiting information of the current condition with a minimal deviation of the network weights. Description of the current conditions is provided by a segmentation fusion scheme, which appropriately combines color and depth information.

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تاریخ انتشار 2003