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.
This thesis proposes a... (more)
|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|
|Note||Masters Thesis Electrical Engineering 2019|
|Collaborating Institutions||Graduate College / ASU Library|
|Additional Formats||MODS / OAI Dublin Core / RIS|