Kernel descriptors provide a unified way to generate rich visual feature sets by turning pixel attributes into patch-level features, and yield impressive results on many object rec...
Liefeng Bo, Kevin Lai, Xiaofeng Ren and Dieter Fox
— Language and image understanding are two major goals of artificial intelligence which can both be conceptually formulated in terms of parsing the input signal into a hierarchi...
Long Zhu, Yuanhao Chen, Yuan Lin, Chenxi Lin, Alan...
We discuss the issues and challenges of generic object recognition. We argue that high-level, volumetric part-based descriptions are essential in the process of recognizing object...
Building of atlases representing average and variability of a population of images or of segmented objects is a key topic in application areas like brain mapping, deformable objec...
Shun Xu, Martin Andreas Styner, Brad Davis, Sarang...
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...