Titlebook: Computer Vision -- ACCV 2014; 12th Asian Conferenc Daniel Cremers,Ian Reid,Ming-Hsuan Yang Conference proceedings 2015 Springer Internation

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Autobiography

艺术

Modeling the Temporality of Saliency,rames. The evolution of stimuli over a period longer than two frames has been largely ignored in saliency research. We argue that considering temporal evolution of trajectory even for a relatively short period can significantly extend the kind of meaningful regions that can be extracted from videos,

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Salient Object Detection Using Window Mask Transferring with Multi-layer Background Contrast,e first one automatically encodes object location prior to predict visual saliency without the requirement of center-biased assumption, while the second one estimates image saliency using contrast with respect to background regions. The proposed framework consists of the following three basic steps:

主讲人

Large Margin Multi-metric Learning for Face and Kinship Verification in the Wild,, most existing metric learning methods only learn one Mahalanobis distance metric from a single feature representation for each face image and cannot deal with multiple feature representations directly. In many face verification applications, we have access to extract multiple features for each fac

Aromatic

A Three-Color Coupled Level-Set Algorithm for Simultaneous Multiple Cell Segmentation and Tracking,introduce “3LS”, an algorithm using only three level sets to segment and track arbitrary number of cells in time-lapse microscopic images. The cell number and positions are determined in the first frame by extracting concave points and fitting ellipses after initial segmentation. We construct a grap

Anthology

OR-PCA with MRF for Robust Foreground Detection in Highly Dynamic Backgrounds,e shows more variations, such as water surface, waving trees, varying illumination conditions, etc. Recently, . (RPCA) shows a very nice framework for moving object detection. The background sequence is modeled by a low-dimensional subspace called . matrix and . constitutes the foreground objects. B

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