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ECCV
2006
Springer
14 years 9 months ago
TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
ICBA
2004
Springer
207views Biometrics» more  ICBA 2004»
14 years 1 months ago
Dynamic Local Feature Analysis for Face Recognition
This paper introduces an innovative method, Dynamic Local Feature Analysis (DLFA), for human face recognition. In our proposed method, the face shape and the facial texture informa...
Johnny Ng, Humphrey Cheung
ICCV
2007
IEEE
14 years 9 months ago
How Good are Local Features for Classes of Geometric Objects
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Michael Stark, Bernt Schiele
ICPR
2010
IEEE
14 years 2 months ago
Object Recognition and Localization Via Spatial Instance Embedding
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
Nazli Ikizler Cinbis, Stan Sclaroff
PSIVT
2009
Springer
400views Multimedia» more  PSIVT 2009»
14 years 2 months ago
Local Image Descriptors Using Supervised Kernel ICA
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
Masaki Yamazaki, Sidney Fels