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» Highly Discriminative Invariant FEatures for Image Matching
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CVPR
2010
IEEE
15 years 6 months ago
The Automatic Design of Feature Spaces for Local Image Descriptors using an Ensemble of Non-linear Feature Extractors
The design of feature spaces for local image descriptors is an important research subject in computer vision due to its applicability in several problems, such as visual classifi...
Gustavo Carneiro
IROS
2006
IEEE
164views Robotics» more  IROS 2006»
15 years 8 months ago
SLAM using Visual Scan-Matching with Distinguishable 3D Points
— Scan-matching based on data from a laser scanner is frequently used for mapping and localization. This paper presents an scan-matching approach based instead on visual informat...
Federico Bertolli, Patric Jensfelt, Henrik I. Chri...
ECCV
2008
Springer
16 years 3 months ago
A Pose-Invariant Descriptor for Human Detection and Segmentation
We present a learning-based, sliding window-style approach for the problem of detecting humans in still images. Instead of traditional concatenation-style image location-based feat...
Zhe Lin, Larry S. Davis
CVPR
2004
IEEE
16 years 4 months ago
Shaping Receptive Fields for Affine Invariance
The Gaussian kernel has played a central role in multi-scale methods for feature extraction and matching. In this paper, a method for shaping the filter using the local image stru...
S. Ravela
FGR
1998
IEEE
170views Biometrics» more  FGR 1998»
15 years 6 months ago
Feature-Point Tracking by Optical Flow Discriminates Subtle Differences in Facial Expression
Current approaches to automated analysis have focused on a small set of prototypic expressions (e.g., joy or anger). Prototypic expressions occur infrequently in everyday life, ho...
Jeffrey F. Cohn, Adena J. Zlochower, James Jenn-Ji...