PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
Rapid advancements in positioning systems and wireless communications enable accurate tracking of continuously moving objects. This development poses new challenges to database te...
Shuqiao Guo, Zhiyong Huang, H. V. Jagadish, Beng C...
Visual codebook based quantization of robust appearance descriptors extracted from local image patches is an effective means of capturing image statistics for texture analysis and...
Human identity recognition is an important yet underaddressed
problem. Previous methods were strictly limited
to high quality photographs, where the principal techniques
heavily...
We propose a joint representation and classification framework that achieves the dual goal of finding the most discriminative sparse overcomplete encoding and optimal classifier p...