文档介绍：P1: IML/FFX P2: IML/FFX QC: IML/FFX T1: IML
MOBK039-FM MOBK039- November 9, 2006 21:41
Tensor Voting
A anization Approach
puter Vision and Machine Learning
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Copyright ©2006 by Morgan & Claypool
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in
any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations
in printed reviews, without the prior permission of the publisher.
Tensor Voting: A anization Approach puter Vision and Machine Learning
Philippos Mordohai and Gerard´ Medioni
ISBN: 1598291009 paperback
ISBN: 15982910099781598291001 paperback
ISBN: 1598291017 ebook
ISBN: 15982910179781598291018 ebook
DOI:
A Publication in the Morgan & Claypool Publishers Series:
SYNTHESIS LECTURES ON IMAGE, VIDEO, AND MULTIMEDIA PROCESSING
Lecture #8
Series Editor: Alan C. Bovik, University of Texas, Austin
ISSN Print 1559-8136 Electronic 1559-8144
First Edition
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P1: IML/FFX P2: IML/FFX QC: IML/FFX T1: IML
MOBK039-FM MOBK039- November 9, 2006 21:41
Tensor Voting
A anization Approach
puter Vision and Machine Learning
Philippos Mordohai
University of North Carolina
Gerard´ Medioni
University of Southern California
SYNTHESIS LECTURES ON IMAGE, VIDEO, AND MULTIMEDIA
PROCESSING #8
M
&C Morgan & Claypool Publishers
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ABSTRACT
This lecture presents research on a general framework for anization that was
conducted mainly at the Institute for Robotics and Intelligent Systems of the University of
Southern California. It is not written as a historical recount of the work, since the sequence of
the presentation is not in chronol