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Published in:
2010 | OriginalPaper | Chapter
Hand Shape Recognition in Real Images Using Hierarchical Temporal Memory Trained on Synthetic Data
Author : Tomasz Kapuściński
Published in: Image Processing and Communications Challenges 2
Publisher: Springer Berlin Heidelberg
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In this paper the generalization capabilities of the Hierarchical Temporal Memory (HTM), the new computing paradigm based on cortical theory, has been exploited in order to recognize the hand shape in real images while training is done on synthetically generated data. It has been shown that the HTM trained in this way and tuned up with a small number of real examples gives pretty good recognition rates. Additionally the good scalability of the proposed solution has been observed while analyzing the recognition rates for the class that is ’almost unknown’ because only few examples are shown during training.