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» Some Solutions to the Missing Feature Problem in Vision
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ICCV
2005
IEEE
14 years 9 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
ICCV
2011
IEEE
12 years 7 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
CVPR
2001
IEEE
14 years 9 months ago
Understanding Popout through Repulsion
Perceptual popout is defined by both feature similarity and local feature contrast. We identify these two measures with attraction and repulsion, and unify the dual processes of a...
Stella X. Yu, Jianbo Shi
3DIM
2011
IEEE
12 years 7 months ago
Finding the Best Feature Detector-Descriptor Combination
Addressing the image correspondence problem by feature matching is a central part of computer vision and 3D inference from images. Consequently, there is a substantial amount of w...
Anders Lindbjerg Dahl, Henrik Aanæs, Kim Ste...
CVPR
2009
IEEE
15 years 2 months ago
Multiple Instance Feature for Robust Part-based Object Detection
Feature misalignment in object detection refers to the phenomenon that features which re up in some positive detection windows do not re up in other pos- itive detection windo...
Zhe Lin (University of Maryland at College Park), ...