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2006

Attention-Based Dynamic Visual Search Using Inner-Scene Similarity: Algorithms and Bounds

8 years 6 months ago
Attention-Based Dynamic Visual Search Using Inner-Scene Similarity: Algorithms and Bounds
A visual search is required when applying a recognition process on a scene containing multiple objects. In such cases, we would like to avoid an exhaustive sequential search. This work proposes a dynamic visual search framework based mainly on innerscene similarity. Given a number of candidates (e.g., sub-images), we hypothesize 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 lin...
Tamar Avraham, Michael Lindenbaum
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where PAMI
Authors Tamar Avraham, Michael Lindenbaum
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