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Performance Evaluation of Object Proposal Generators for Salient Object Detection

Abstract The detection and segmentation of objects appearing in a natural scene, often referred to as Object Detection, has gained a lot of interest in the computer vision field. Although most existing object detectors aim to detect all the objects in a given scene, it is important to evaluate whether these methods are capable of detecting the salient objects in the scene when constraining the number of proposals that can be generated due to constraints on timing or computations during execution. Salient objects are objects that tend to be more fixated by human subjects. The detection of salient objects is important in applications such as image collection browsing, image display on small devices, and perceptual compression.

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Created Date 2019
Contributor Kotamraju, Sai Prajwal (Author) / Karam, Lina J (Advisor) / Yu, Hongbin (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Computer science / Image Saliency / Object Detection / Object Proposal Generation / Salient Object Detection
Type Masters Thesis
Extent 70 pages
Language English
Note Masters Thesis Electrical Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis