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Efficient detection and reliable matching of image features constitute a fundamental task in computer vision. When real-time operation is required, the solution to this problem becomes a real challenge, because of increased processing requirements. Scale Invariant Feature Transform (SIFT) is considered as a stable and robust algorithm for the extraction of invariant features, however special hardware...
RANSAC is a popular and robust fitting algorithm. In the field of image processing, RANSAC can be successfully used to reject false correspondences between similar images. Due to its iterative nature, RANSAC is computationally demanding and time consuming. When the target application operates in real-time, conventional approaches based on personal computers usually fail to meet the requirements. In...
A new architecture for the real-time detection of scale-invariant features in image sequences is presented. The system is based on a low-cost smart-camera custom board, developed to target robotic vision applications. Several optimizations of the SIFT detection procedure are proposed in order to achieve robust keypoint detection with high repeatability and recall values. As a result, a high accuracy...
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