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   <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">Dunagan, Brian Kerry, 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">2005-09-26T20:11:32Z</dim:field>
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   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (M. Eng. and S.B.)--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 (leaves 49-50).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">With the dramatic fall in price of electronics over the past several years, large-scale networks of sensors are steadily becoming more feasible. The goal of this research project was to deploy a sensor network for data collection of human trajectories and to develop and test a method for taking walls into account using a penalty function in an ongoing research project in trajectory tracking model. There were two deployed sensor networks, one with distance sensors and one with cameras, and the camera network was used to collect data for the two papers. The trajectory tracking model was modified to incorporate wall constraints to enable exploration of more realistic scenarios, with encouraging preliminary results.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Brian Kerry Dunagan.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.B.</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">Tracking with constraints in a web of sensors</dim:field>
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   	&lt;Title>Tracking with constraints in a web of sensors&lt;/Title>
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   	&lt;Abstract>With the dramatic fall in price of electronics over the past several years, large-scale networks of sensors are steadily becoming more feasible. The goal of this research project was to deploy a sensor network for data collection of human trajectories and to develop and test a method for taking walls into account using a penalty function in an ongoing research project in trajectory tracking model. There were two deployed sensor networks, one with distance sensors and one with cameras, and the camera network was used to collect data for the two papers. The trajectory tracking model was modified to incorporate wall constraints to enable exploration of more realistic scenarios, with encouraging preliminary results.&lt;/Abstract>
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