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ICIP
2007
IEEE
14 years 9 months ago
MuFeSaC: Learning When to Use Which Feature Detector
Interest point detectors are the starting point in image analysis for depth estimation using epipolar geometry and camera ego-motion estimation. With several detectors defined in ...
Sreenivas R. Sukumar, David L. Page, Hamparsum Boz...
DPHOTO
2009
353views Hardware» more  DPHOTO 2009»
13 years 5 months ago
Fuzzy-based motion estimation for video stabilization using SIFT interest points
In this paper we present a technique which infers interframe motion by tracking SIFT features through consecutive frames: feature points are detected and their stability is evalua...
Sebastiano Battiato, Giovanni Gallo, Giovanni Pugl...
PR
2008
173views more  PR 2008»
13 years 8 months ago
Object recognition using a generalized robust invariant feature and Gestalt's law of proximity and similarity
In this paper, we propose a new context-based method for object recognition. We first introduce a neuro-physiologically motivated visual part detector. We found that the optimal f...
Sungho Kim, Kuk-Jin Yoon, In-So Kweon
PAMI
2002
112views more  PAMI 2002»
13 years 7 months ago
Recognizing Handwritten Digits Using Hierarchical Products of Experts
The product of experts learning procedure [1] can discover a set of stochastic binary features that constitute a nonlinear generative model of handwritten images of digits. The qua...
Guy Mayraz, Geoffrey E. Hinton
PAMI
2007
161views more  PAMI 2007»
13 years 7 months ago
High-Performance Rotation Invariant Multiview Face Detection
Abstract—Rotation invariant multiview face detection (MVFD) aims to detect faces with arbitrary rotation-in-plane (RIP) and rotationoff-plane (ROP) angles in still images or vide...
Chang Huang, Haizhou Ai, Yuan Li, Shihong Lao