On the relative complexity of active vs. passive visual search
International Journal of Computer Vision
International Journal of Computer Vision
Promising directions in active vision
International Journal of Computer Vision
Control of selective perception using Bayes nets and decision theory
International Journal of Computer Vision - Special issue on active vision II
Using intermediate objects to improve the efficiency of visual search
International Journal of Computer Vision - Special issue on active vision II
An active vision architecture based on iconic representations
Artificial Intelligence - Special volume on computer vision
Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
Active object recognition integrating attention and viewpoint control
Computer Vision and Image Understanding
Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Learning for View-Based Human Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object selection based on oscillatory correlation
Neural Networks
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
A reinforcement learning model of selective visual attention
Proceedings of the fifth international conference on Autonomous agents
A Maximum-Likelihood Strategy for Directing Attention during Visual Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Real-Time Face Detection
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
IEEE Transactions on Image Processing
An efficient algorithm for attention-driven image interpretation from segments
Pattern Recognition
Spatiotemporal saliency for video classification
Image Communication
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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 inner-scene similarity. Given a number of candidates (e.g., subimages), 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 linear estimation. Several experiments are presented in which the statistical characteristics, search algorithm, and bound are evaluated and verified.