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...
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
In recent years, large databases of natural images have
become increasingly popular in the evaluation of face and
object recognition algorithms. However, Pinto et al. previously
...
Recently, the wide deployment of practical face recognition systems gives rise to the emergence of the inter-modality face recognition problem. In this problem, the face images in ...
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...