DocumentCode :
640091
Title :
Two-dimensional visual search
Author :
Naghshvar, Mohammad ; Javidi, Tara
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of California San Diego, La Jolla, CA, USA
fYear :
2013
fDate :
7-12 July 2013
Firstpage :
1262
Lastpage :
1266
Abstract :
Consider the problem of sequentially searching for a single target in an image. Let the image be divided into M × M equal sized segments where M determines the resolution of the search. The goal is to find the segment that contains the target quickly and accurately. In each step, the player can visually inspect an allowable combination of the segments, and the outcome of the inspection is noisy. In this paper, a lower bound on the optimal total cost is derived. Furthermore, two heuristic policies are considered: A policy that visually inspects a segment with the highest probability of having the target; and a policy that in each step inspects a combination that maximizes the Extrinsic Jensen- Shannon divergence. Via numerical and asymptotic analysis, the performance of the above policies are investigated.
Keywords :
costing; image resolution; image segmentation; inspection; numerical analysis; probability; asymptotic analysis; extrinsic Jensen-Shannon divergence; heuristic policy; image resolution; image segmentation; inspection; numerical analysis; probability; two-dimensional visual search; Image segmentation; Information theory; Inspection; Search problems; Upper bound; Vectors; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on
Conference_Location :
Istanbul
ISSN :
2157-8095
Type :
conf
DOI :
10.1109/ISIT.2013.6620429
Filename :
6620429
Link To Document :
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