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ISVC
2010
Springer

Attention-Based Target Localization Using Multiple Instance Learning

9 years 10 months ago
Attention-Based Target Localization Using Multiple Instance Learning
Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic regression MIL algorithm using log covariance features to automatically learn the model of a target that persists across input frames. The approach makes no assumptions about the target’s motion model and can be used to learn models for multiple targets present in the scene. The learned target models can also be updated in an online manner. We demonstrate the validity and usefulness of the proposed approach to localize targets in various scenes using commercial-grade surveillance cameras. We also demonstrate its applicability to bootstrap conventional tracking systems and show that automatic initialization using our technique helps to achieve superior performance.
Karthik Sankaranarayanan, James W. Davis
Added 28 Jan 2011
Updated 28 Jan 2011
Type Journal
Year 2010
Where ISVC
Authors Karthik Sankaranarayanan, James W. Davis
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