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» Matching images more efficiently with local descriptors
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ICIP
2002
IEEE
14 years 9 months ago
A new and simple shape descriptor based on a non-parametric multiscale model
In this paper, we present a new and robust shape descriptor, which can be efficiently used to quickly prune a search for similar shapes in a large image database. The proposed sha...
Max Mignotte
ECCV
2008
Springer
14 years 9 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
2011
IEEE
13 years 2 months ago
Learning and Matching Multiscale Template Descriptors for Real-Time Detection, Localization and Tracking
We describe a system to learn an object template from a video stream, and localize and track the corresponding object in live video. The template is decomposed into a number of lo...
Taehee Lee, Stefano Soatto
ICCV
2007
IEEE
14 years 9 months ago
Discriminant Embedding for Local Image Descriptors
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and visual recognition. However, such descriptors are generally par...
Gang Hua, Matthew Brown, Simon A. J. Winder
CVPR
2010
IEEE
13 years 12 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