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» Learning Visual Invariance
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ICML
2005
IEEE
14 years 9 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
ICML
2004
IEEE
14 years 9 months ago
Generative modeling for continuous non-linearly embedded visual inference
Many difficult visual perception problems, like 3D human motion estimation, can be formulated in terms of inference using complex generative models, defined over high-dimensional ...
Cristian Sminchisescu, Allan D. Jepson
CVPR
2010
IEEE
14 years 4 months ago
The Role of Features, Algorithms and Data in Visual Recognition
There are many computer vision algorithms developed for visual (scene and object) recognition. Some systems focus on involved learning algorithms, some leverage millions of trainin...
Devi Parikh and C. Lawrence Zitnick
TOOLS
1999
IEEE
14 years 18 days ago
Constraint Diagrams: A Step Beyond UML
The Unified Modeling Language (UML) is a set of notations for modelling object-oriented systems. It has become the de facto standard. Most of its notations are diagrammatic. An ex...
Joseph Gil, John Howse, Stuart Kent
ASSETS
2007
ACM
14 years 10 days ago
Accessible spaces: navigating through a marked environment with a camera phone
We demonstrate a system designed to assist a visually impaired individual while moving in an unfamiliar environment. Small and economical color markers are placed in key locations...
Kee-Yip Chan, Roberto Manduchi, James Coughlan