<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T06:48:32Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/17985" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/17985</identifier><datestamp>2022-01-13T07:54:29Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Trevor Darrell.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Sundberg, Patrik P. (Patrik Per), 1980-</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2005-06-02T19:30:52Z</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2004</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2004</dim:field>
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   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">57189733</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 57-58).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">In this thesis, I implemented and extended a face detector, based on cascades of boosted features, for use in real time systems. The extensions are twofold. First, I designed a way of combining several cascades into a cascade tree, and showed how such a tree provides a powerful mechanism for combining detector efficiency and accuracy. When the training data has large variations, the cascade tree yields a faster detector, and when the data has only small variations, there is a distinct detection rate improvement. As a second extension, I designed a system for pose estimation based on an array of cascades. I performed an evaluation of this system and compared to normalized cross-correlation.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Patrik Sundberg.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">58 p.</dim:field>
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   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.</dim:field>
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   <dim:field mdschema="dc" element="subject" lang="en_US">Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Pose estimation using cascade trees</dim:field>
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   	&lt;Title>Pose estimation using cascade trees&lt;/Title>
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   	&lt;PublicationDate>2004&lt;/PublicationDate>
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   	&lt;Abstract>In this thesis, I implemented and extended a face detector, based on cascades of boosted features, for use in real time systems. The extensions are twofold. First, I designed a way of combining several cascades into a cascade tree, and showed how such a tree provides a powerful mechanism for combining detector efficiency and accuracy. When the training data has large variations, the cascade tree yields a faster detector, and when the data has only small variations, there is a distinct detection rate improvement. As a second extension, I designed a system for pose estimation based on an array of cascades. I performed an evaluation of this system and compared to normalized cross-correlation.&lt;/Abstract>
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