We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
In this paper we present a statistical learning scheme for image classification based on a mixture of old fashioned ideas and state of the art learning tools. We represent input i...
Object pose (location and orientation) estimation is a
common task in many computer vision applications. Although
many methods exist, most algorithms need manual
initialization ...
Marcel Germann, Michael D. Breitenstein, In Kyu Pa...
In this paper, we propose a new algorithm that solves both the stereo matching and the image denoising problem simultaneously for a pair of noisy stereo images. Most stereo algorit...
Yong Seok Heo (Seoul National University), Kyoung ...
We present a novel reranking framework for Content Based Image Retrieval (CBIR) systems based on con-textual dissimilarity measures. Our work revisit and extend the method of Perro...