This paper studies the problem of learning a full range of pairwise affinities gained by integrating local grouping cues for spectral segmentation. The overall quality of the spect...
Tae Hoon Kim (Seoul National University), Kyoung M...
⎯This paper presents an improved multi-object segmentation algorithm based on probabilistic labeling. First, a critical look is focused on utilizing vector calculus operator and ...
We propose a fully automatic method for summarizing and indexing unstructured presentation videos based on text extracted from the projected slides. We use changes of text in the ...
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...