Sciweavers

DAGM
2006
Springer
13 years 8 months ago
Exploiting Low-Level Image Segmentation for Object Recognition
Abstract. A method for exploiting the information in low-level image segmentations for the purpose of object recognition is presented. The key idea is to use a whole ensemble of se...
Volker Roth, Björn Ommer
MM
2006
ACM
168views Multimedia» more  MM 2006»
13 years 10 months ago
Scalability of local image descriptors: a comparative study
Computer vision researchers have recently proposed several local descriptor schemes. Due to lack of database support, however, these descriptors have only been evaluated using sma...
Herwig Lejsek, Friðrik Heiðar Ásmun...
IPPS
2006
IEEE
13 years 10 months ago
Acceleration of a content-based image-retrieval application on the RDISK cluster
Because of the growing use of multimedia content over Internet, Content-Based Image Retrieval (CBIR) has recently received a lot of interest. While accurate search techniques base...
Auguste Noumsi, Steven Derrien, Patrice Quinton
AMR
2007
Springer
197views Multimedia» more  AMR 2007»
13 years 10 months ago
How to Use SIFT Vectors to Analyze an Image with Database Templates
During last years, local image descriptors have received much attention because of their efficiency for several computer vision tasks such as image retrieval, image comparison, fea...
Adrien Auclair, Laurent D. Cohen, Nicole Vincent
ICPR
2008
IEEE
13 years 11 months ago
Combining local descriptors for 3D object recognition and categorization
Various local descriptors have been used successfully in a variety of tasks including object recognition. Although different descriptors have been shown to have different strength...
Andrea Salgian
PSIVT
2009
Springer
400views Multimedia» more  PSIVT 2009»
13 years 11 months ago
Local Image Descriptors Using Supervised Kernel ICA
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
Masaki Yamazaki, Sidney Fels
ICPR
2006
IEEE
14 years 5 months ago
Image Categorization Using Local Probabilistic Descriptors
Image categorization involves the well known difficulties with different visual appearances of a single object, but introduces also the problem of within-category variation. This ...
Dorian Suc, Jasna Maver, Katarina Mele
ECCV
1996
Springer
14 years 6 months ago
Stereo Without Search
Search is not inherent in the correspondence problem. We propose a representation of images, called intrinsic curves, that combines the ideas of associative storage of images with...
Carlo Tomasi, Roberto Manduchi
ICCV
2007
IEEE
14 years 6 months ago
How Good are Local Features for Classes of Geometric Objects
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Michael Stark, Bernt Schiele
CVPR
2008
IEEE
14 years 6 months ago
In defense of Nearest-Neighbor based image classification
State-of-the-art image classification methods require an intensive learning/training stage (using SVM, Boosting, etc.) In contrast, non-parametric Nearest-Neighbor (NN) based imag...
Oren Boiman, Eli Shechtman, Michal Irani