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

OVERT

Introduction to Cytochemical Bioassay,f foreground detection and the computation time as well. Moreover, solving MRF with graph-cuts exploits structural information using spatial neighborhood system and similarities to further improve the foreground segmentation in highly dynamic backgrounds. Experimental results on challenging datasets

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Brochure

尽忠

Local Generic Representation for Face Recognition with Single Sample per Person,ations of a query sample by the gallery samples. Considering the fact that different parts of human faces have different importance to face recognition, and the fact that the intra-class facial variations can be shared across different subjects, we propose a local generic representation (LGR) based

APNEA

Unsupervised Image Co-segmentation Based on Cooperative Game,ation algorithms have the assumptions that the common objects are singletons or with the similar size. In addition, they might assume that the background features are simple or discriminative. This paper presents a cooperative co-segmentation without these assumptions. In the proposed cooperative co

骇人

obeisance

Real-Time Head Orientation from a Monocular Camera Using Deep Neural Network,and we exploit the architecture in a data regression manner to learn the mapping function between visual appearance and three dimensional head orientation angles. Therefore, in contrast to classification based approaches, our system outputs continuous head orientation. The algorithm uses convolution

incarcerate

金哥占卜者

Visual Salience Learning via Low Rank Matrix Recovery,ehave differently over an individual image, and these saliency detection results often complement each other. To make full use of the advantages of the existing saliency detection methods, in this paper, we propose a salience learning model which combines various saliency detection methods such that

缓解

A New Framework for Multiclass Classification Using Multiview Assisted Adaptive Boosting,classifiers on each view and finally conglomerate them using weighted summation. Such approaches are void from inter-view communications and thus do not guarantee to yield the best possible ensemble classifier on the given sample-view space. This paper proposes a new algorithm for multiclass classif