Visual Object Recognition, Kristen Grauman
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Mor g a n C l aypool Pu b l i s h e r s
&
w w w . m o r g a n c l a y p o o l . c o m
Series Editors:
Ronald J. Brachman, Yahoo! Research and Thomas G. Dietterich, Oregon State University
MOR G A N &C L AY P OOL
C
M
&
Mor g a n C l ay p o ol Publishers
&
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
About SYNTHESIs
This volume is a printed version of a work that appears in the Synthesis
Digital Library of Engineering and Computer Science. Synthesis Lectures
provide concise, original presentations of important research and development
topics, published quickly, in digital and print formats. For more information
visit www.morganclaypool.com
Ronald J. Brachman and Thomas G. Dietterich, Series Editors
ISBN: 978-1-59829-968-7
9 78 1 598 299687
9 0 000
Series ISSN: 1939-4608
VISUAL OBJECT RECOGNITION
GRAUMAN • LEIBE
Visual Object Recognition
Kristen Grauman, University of Texas at Austin
Bastian Leibe, RWTH Aachen University
The visual recognition problem is central to computer vision research. From robotics to information
retrieval, many desired applications demand the ability to identify and localize categories, places,
and objects. This tutorial overviews computer vision algorithms for visual object recognition and
image classification. We introduce primary representations and learning approaches, with an emphasis
on recent advances in the field. The target audience consists of researchers or students working in
AI, robotics, or vision who would like to understand what methods and representations are available
for these problems. This lecture summarizes what is and isn’t possible to do reliably today, and
overviews key concepts that could be employed in systems requiring visual categorization.
Visual Object
Recognition
Kristen Grauman
Bastian Leibe
Mor g a n C l aypool Pu b l i s h e r s
&
w w w . m o r g a n c l a y p o o l . c o m
Series Editors:
Ronald J. Brachman, Yahoo! Research and Thomas G. Dietterich, Oregon State University
MOR G A N &C L AY P OOL
C
M
&
Mor g a n C l ay p o ol Publishers
&
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
About SYNTHESIs
This volume is a printed version of a work that appears in the Synthesis
Digital Library of Engineering and Computer Science. Synthesis Lectures
provide concise, original presentations of important research and development
topics, published quickly, in digital and print formats. For more information
visit www.morganclaypool.com
Ronald J. Brachman and Thomas G. Dietterich, Series Editors
ISBN: 978-1-59829-968-7
9 78 1 598 299687
9 0 000
Series ISSN: 1939-4608
VISUAL OBJECT RECOGNITION
GRAUMAN • LEIBE
Visual Object Recognition
Kristen Grauman, University of Texas at Austin
Bastian Leibe, RWTH Aachen University
The visual recognition problem is central to computer vision research. From robotics to information
retrieval, many desired applications demand the ability to identify and localize categories, places,
and objects. This tutorial overviews computer vision algorithms for visual object recognition and
image classification. We introduce primary representations and learning approaches, with an emphasis
on recent advances in the field. The target audience consists of researchers or students working in
AI, robotics, or vision who would like to understand what methods and representations are available
for these problems. This lecture summarizes what is and isn’t possible to do reliably today, and
overviews key concepts that could be employed in systems requiring visual categorization.
Visual Object
Recognition
Kristen Grauman
Bastian Leibe
Mor g a n C l aypool Pu b l i s h e r s
&
w w w . m o r g a n c l a y p o o l . c o m
Series Editors:
Ronald J. Brachman, Yahoo! Research and Thomas G. Dietterich, Oregon State University
MOR G A N &C L AY P OOL
C
M
&
Mor g a n C l ay p o ol Publishers
&
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
About SYNTHESIs
This volume is a printed version of a work that appears in the Synthesis
Digital Library of Engineering and Computer Science. Synthesis Lectures
provide concise, original presentations of important research and development
topics, published quickly, in digital and print formats. For more information
visit www.morganclaypool.com
Ronald J. Brachman and Thomas G. Dietterich, Series Editors
ISBN: 978-1-59829-968-7
9 78 1 598 299687
9 0 000
Series ISSN: 1939-4608
VISUAL OBJECT RECOGNITION
GRAUMAN • LEIBE
Visual Object Recognition
Kristen Grauman, University of Texas at Austin
Bastian Leibe, RWTH Aachen University
The visual recognition problem is central to computer vision research. From robotics to information
retrieval, many desired applications demand the ability to identify and localize categories, places,
and objects. This tutorial overviews computer vision algorithms for visual object recognition and
image classification. We introduce primary representations and learning approaches, with an emphasis
on recent advances in the field. The target audience consists of researchers or students working in
AI, robotics, or vision who would like to understand what methods and representations are available
for these problems. This lecture summarizes what is and isn’t possible to do reliably today, and
overviews key concepts that could be employed in systems requiring visual categorization.
Visual Object
Recognition
Kristen Grauman
Bastian Leibe
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