C++ Library for tasks frequently encountered in high-level computer vision systems for object recognition and image classification. The library contains the following features
Machine Learning: k-means clustering, nn/soft vector quantization and histograms, mean shift clustering, randomized decision tree ensembles, structured support vector machine training, conditional random field (MAP-MRF inference).
Image Features: adaptive color histograms (CIE LAB, HSV, RGB), canny edge detection, histogram of oriented gradients (HoG), local binary patterns (LBP), local self-similarity (LSS), oriented gradient histograms, semantic texton forests, region covariance, textons.
High-level Image Processing: mean shift segmentation, tree-based segmentation (FH), normalized cut image segmentation, image laplacians: matting laplacian, intervening contours, gradient
- Changes to previous version:
Initial Announcement on mloss.org.
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