Currently available tracking systems need some kinds of attachments on the objects to be tracked. Barcodes, RFID tags, GPS modules are a few examples of these attachments. In addition, these attachments make the object to realize that its being tracked. To overcome these limitations, we need a system that is capable of tracking the objects without installing any physical components on it. This research evaluates the potential of using stationary cameras for tagless tracking with the help of computer vision techniques.
June 30, 2015
The right to download or print any of the pages of this thesis (Material) is granted by the copyright owner only for personal or classroom use. The author retains all proprietary rights, including copyright ownership. Any reproduction or editing or other use of this Material by any means requires the express written permission of the copyright owner. Except as provided above, or any use beyond what is allowed by fair use (Title 17 Section 107 U.S.C.), you may not reproduce, republish, post, transmit or distribute any Material from this web site in any physical or digital form without the permission of the copyright owner of the Material. Inquiries regarding any further use of these materials should be addressed to Administration, Jernigan Library, Texas A&M University-Kingsville, 700 University Blvd. Kingsville, Texas 78363-8202, (361)593-3416.