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» Object Recognition from Local Scale-Invariant Features
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BMVC
2010
14 years 7 months ago
Weakly Supervised Object Recognition and Localization with Invariant High Order Features
High order features have been proposed to incorporate geometrical information into the "bag of feature" representation. We propose algorithms to perform fast weakly supe...
Yimeng Zhang, Tsuhan Chen
DAGM
2004
Springer
15 years 2 months ago
Scale-Invariant Object Categorization Using a Scale-Adaptive Mean-Shift Search
The goal of our work is object categorization in real-world scenes. That is, given a novel image we want to recognize and localize unseen-before objects based on their similarity t...
Bastian Leibe, Bernt Schiele
CVIU
2010
429views more  CVIU 2010»
14 years 9 months ago
Cascade of descriptors to detect and track objects across any network of cameras
Most multi-camera systems assume a well structured environment to detect and track objects across cameras. Cameras need to be fixed and calibrated, or only objects within a traini...
Alexandre Alahi, Pierre Vandergheynst, Michel Bier...
CVPR
2003
IEEE
15 years 11 months ago
Multi-scale Phase-based Local Features
Local feature methods suitable for image feature based object recognition and for the estimation of motion and structure are composed of two steps, namely the `where' and `wh...
Gustavo Carneiro, Allan D. Jepson
ICIAR
2010
Springer
15 years 2 months ago
Adaptation of SIFT Features for Robust Face Recognition
Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The origina...
Janez Krizaj, Vitomir Struc, Nikola Pavesic