In this paper, we propose a new object detection method that does not need a learning mechanism. Given a hand-drawn model as a query, we can detect and locate objects that are sim...
Chih-Wen Su, Mark Liao, Yu-Ming Liang, Hsiao-Rong ...
Background: The expansion of automatic imaging technologies has created a need to be able to efficiently compare and review large sets of image data. To enable comparisons of imag...
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
Abstract--This work is dedicated to a statistical trajectorybased approach addressing two issues related to dynamic video content understanding: recognition of events and detection...
Alexandre Hervieu, Patrick Bouthemy, Jean-Pierre L...
We address the problem of regional color transfer between two natural images by probabilistic segmentation. We use a new Expectation-Maximization (EM) scheme to impose both spatia...