2026-09-18T18:24:55Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/16499 2023-07-10 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Huang, Thomas S. Stieber, Brian M. 2010-06-22T19:46:42Z 2010-06-22T19:46:42Z 2010-06-22T19:46:42Z This is a study of viewpoint invariant appearance models for pedestrian recognition. The study investigates basic models, color histograms and region based histograms, to gain intuition about the appearance models as well as create new baseline results for evaluating future appearance models. This insight is then used to create an appearance model based on large-margin nearest-neighbor classication. This model significantly outperforms the current state of the art. Finally, the IFP Image Processor, a basic framework for implementation of surveillance systems algorithms, is introduced. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2010-04-17T20:50:30Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 4 Stieber_Brian.pdf: 1613673 bytes, checksum: 84139e968d3deed1a3aa85da8c336908 (MD5) ecethesis.tex: 60189 bytes, checksum: 3ec8a7d4ad79b63bfe20fa603aa97ee7 (MD5) Stieber_Brian.pdf: 1613673 bytes, checksum: ffb26298d2d961dc4bbffdabd0c55c94 (MD5) References.bib: 10637 bytes, checksum: 405c1f16d2c054e79e2849fc9f4da922 (MD5) Made available in DSpace on 2010-06-22T19:46:42Z (GMT). No. of bitstreams: 5 Stieber_Brian.pdf: 1613673 bytes, checksum: 84139e968d3deed1a3aa85da8c336908 (MD5) ecethesis.tex: 60189 bytes, checksum: 3ec8a7d4ad79b63bfe20fa603aa97ee7 (MD5) 1_Stieber_Brian.pdf: 1613673 bytes, checksum: ffb26298d2d961dc4bbffdabd0c55c94 (MD5) References.bib: 10637 bytes, checksum: 405c1f16d2c054e79e2849fc9f4da922 (MD5) license.txt: 4063 bytes, checksum: 8f410d1e38d7ab59aaf001d3c6d9278a (MD5) http://hdl.handle.net/2142/16499 en Copyright 2010 Brian M. Stieber viewpoint invariant pedestrian recognition non-overlapping cameras large margin nearest neighbor An investigation into viewpoint invariant pedestrian recognition for surveillance systems 2010-5 Electrical & Computer Eng 1933 Electrical & Computer Engr 1200 University of Illinois at Urbana-Champaign Thesis M.S. MS:Electr & Computer Eng-UIUC 10KS1200MS