We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
We propose a novel feature-based image registration method using both the local and global structures of the feature points. To address various imaging conditions, we improve the l...
Local features are widely used for content-based image retrieval and object recognition. We present an efficient method for encoding digital images suitable for local feature extr...
Mina Makar, Chuo-Ling Chang, David M. Chen, Sam S....
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of ...