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» Object of Interest Detection by Saliency Learning
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CVPR
2012
IEEE
13 years 1 days ago
Boosting bottom-up and top-down visual features for saliency estimation
Despite significant recent progress, the best available visual saliency models still lag behind human performance in predicting eye fixations in free-viewing of natural scenes. ...
Ali Borji
GECCO
2008
Springer
239views Optimization» more  GECCO 2008»
14 years 10 months ago
Multiobjective design of operators that detect points of interest in images
In this paper, a multiobjective (MO) learning approach to image feature extraction is described, where Pareto-optimal interest point (IP) detectors are synthesized using genetic p...
Leonardo Trujillo, Gustavo Olague, Evelyne Lutton,...
CVPR
2004
IEEE
15 years 1 months ago
Scale-Invariant Shape Features for Recognition of Object Categories
We introduce a new class of distinguished regions based on detecting the most salient convex local arrangements of contours in the image. The regions are used in a similar way to ...
Frédéric Jurie, Cordelia Schmid
ICML
2005
IEEE
15 years 10 months ago
Q-learning of sequential attention for visual object recognition from informative local descriptors
This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
Lucas Paletta, Gerald Fritz, Christin Seifert
ETRA
2008
ACM
235views Biometrics» more  ETRA 2008»
14 years 11 months ago
Using semantic content as cues for better scanpath prediction
Under natural viewing conditions, human observers use shifts in gaze to allocate processing resources to subsets of the visual input. There are many computational models that try ...
Moran Cerf, E. Paxon Frady, Christof Koch