# Technical Report CIS-2003-02

 TR#: CIS-2003-02 Class: CIS Title: Attention-based Dynamic Visual search using Inner Scene Similarity: Algorithms and Bounds Authors: Tamar Avraham and Michael Lindenbaum PDF CIS-2003-02.pdf PDF - Revised CIS-2003-02.revised.pdf Abstract: Visual search is required when applying a recognition process on a scene containing multiple objects. In such a case, we would like to avoid an exhaustive sequential search. This work proposes a dynamic visual search framework based mainly on inner-scene similarity. Given a number of candidates (e.g. sub-images), our basic hypothesis is that more visually similar candidates are more likely to have the same identity. We use this assumption for determining the order of attention. Both deterministic and stochastic approaches, relying on this hypothesis, are considered. Under the deterministic approach, we suggest a measure similar to Kolmogorov's $\epsilon$-covering that quantifies the difficulty of a search task. We show that this measure bounds the performance of all search algorithms and suggest a simple algorithm that meets this bound. Under the stochastic approach, we model the identity of the candidates as a set of correlated random variables and derive a search procedure based on linear estimation. Several experiments were conducted where the statistical characteristics, the search algorithm, and the bound are evaluated and verified. Copyright The above paper is copyright by the Technion, Author(s), or others. Please contact the author(s) for more information

Remark: Any link to this technical report should be to this page (http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-info.cgi/2003/CIS/CIS-2003-02), rather than to the URL of the PDF files directly. The latter URLs may change without notice.