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» Learning Models for Object Recognition
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ICCV
2005
IEEE
15 years 3 days ago
A Maximum Entropy Framework for Part-Based Texture and Object Recognition
This paper presents a probabilistic part-based approach for texture and object recognition. Textures are represented using a part dictionary found by quantizing the appearance of ...
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce
ECCV
2010
Springer
14 years 3 months ago
Object, Scene and Actions: Combining Multiple Features for Human Action Recognition
Abstract. In many cases, human actions can be identified not only by the singular observation of the human body in motion, but also properties of the surrounding scene and the rel...
ICPR
2002
IEEE
14 years 11 months ago
View-Based Dynamic Object Recognition Based on Human Perception
Psychophysical studies have shown that humans actively exploit temporal information such as contiguity of images in object recognition. We have recently developed a recognition sy...
Arnulf B. A. Graf, Christian Wallraven, Heinrich H...
ICDAR
2003
IEEE
14 years 3 months ago
Learning the lexicon from raw texts for open-vocabulary Korean word recognition
In this paper, we propose a novel method of building a language model for open-vocabulary Korean word recognition. Due to the complex morphology of Korean, it is inappropriate to ...
Sungho Ryu, Jin Hyung Kim
ICDAR
2003
IEEE
14 years 3 months ago
Engineering Drawings Recognition Using a Case-based Approach
In this paper, we propose a framework for engineering drawings recognition using a case-based approach. The key idea of our scheme is that, interactively, the user provides an exa...
Yan Luo, Liu Wenyin