Traditional supervised visual learning simply asks annotators “what” label an image should have. We propose an approach for image classification problems requiring subjective...
We present a new, block-based image codec based on sparse representations using a learned, structured dictionary called the IterationTuned and Aligned Dictionary (ITAD). The quest...
— This paper addresses the design of a control law for vision-based robot navigation. The method proposed is based on a topological representation of the environment. Within this...
The Bag-of-visual Words (BoW) image representation has been applied for various problems in the fields of multimedia and computer vision. The basic idea is to represent images as ...
Shiliang Zhang, Qi Tian, Gang Hua, Qingming Huang,...
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...