We present a new class of statistical models for part-based object recognition. These models are explicitly parametrized according to the degree of spatial structure that they can ...
David J. Crandall, Pedro F. Felzenszwalb, Daniel P...
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
From a conceptual point of view, belief revision and learning are quite similar. Both methods change the belief state of an intelligent agent by processing incoming information. Ho...
Thomas Leopold, Gabriele Kern-Isberner, Gabriele P...
In this article we proposed an improved SIFT-based object recognition methodology for robot applications. This methodology is employed for implementing a robot-head detection syste...
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...