GPU-Based Optimization of Self-Organizing Map Feature Matching for Real-Time Stereo Vision
نویسندگان
چکیده
منابع مشابه
Stereo matching based on the self-organizing feature-mapping algorithm
This paper presents an approach to the local stereo matching problem using edge segments as features with several attributes. We have verified that the differences in attributes for the true matches cluster in a cloud around a center. The correspondence is established on the basis of the minimum squared Mahalanobis distance between the difference of the Ž . attributes for a current pair of feat...
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The feature map represented by the set of weight vectors of the basic SOM (Self-Organizing Map) provides a good approximation to the input space from which the sample vectors come. But the timedecreasing learning rate and neighborhood function of the basic SOM algorithm reduce its capability to adapt weights for a varied environment. In dealing with non-stationary input distributions and changi...
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This paper elaborates on the possibility to leverage the highly parallel nature of GPUs to implement more efficient stereo matching algorithms. Different algorithms have been implemented and compared on the CPU and the GPU in order to show the speedup gained by moving the computation to the graphics card. The results were evaluated for accuracy using the test available on the Middlebury website...
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This PhD aims at the design and implementation of real-time hardware-based stereo vision systems. Stereo vision deals with images acquired by a stereo camera setup, where the disparity between the stereo images allows depth estimation within a scene. In the first part of my research a new hardwareefficient real time disparity map computation module was developed which involved a fully parallel-...
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ژورنال
عنوان ژورنال: Journal of information and communication convergence engineering
سال: 2014
ISSN: 2234-8255
DOI: 10.6109/jicce.2014.12.2.128