Bottom-up, fully unsupervised segmentation remains a daunting challenge for computer vision. In the cosegmentation context, on the other hand, the availability of multiple images ...
In state-of-the-art image retrieval systems, an image is
represented by a bag of visual words obtained by quantizing
high-dimensional local image descriptors, and scalable
schem...
Zhong Wu (Tsinghua University), Qifa Ke (Microsoft...
Spectral clustering and eigenvector-based methods have become increasingly popular in segmentation and recognition. Although the choice of the pairwise similarity metric (or affin...
In this paper, we propose a novel local steerable phase (LSP) feature extracted from the face image using steerable filter for face representation and recognition. Steerable filte...
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...