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Parallel and Distributed Object Recognition

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dc.contributor.author Abualkibash, Munther Hamad en_US
dc.contributor.author El-Sayed, Ahmed en_US
dc.contributor.author Mahmood, Ausif en_US
dc.date.accessioned 2014-07-16T16:49:24Z
dc.date.available 2014-07-16T16:49:24Z
dc.date.issued 2012 en_US
dc.identifier.citation Poster 40 en_US
dc.identifier.other d105e6cc-ab0f-5999-1cd6-793af735795e en_US
dc.identifier.uri https://scholarworks.bridgeport.edu/xmlui/handle/123456789/682
dc.description.abstract This poster presents a parallel implementation of an object detection algorithm, as well as an improved pruning technique, which is an important part in an object detection implementation. We focus on face detection, even though the techniques developed are applicable to object detection in general. We implement the well known face detection algorithm of Viola-Jones and parallelize the important steps, and then come up with a better pruning algorithm when many nearby windows indicate a detection. We also consider the effect of multiple scales and present a pruning algorithm that minimizes the detected windows such that a single window indicating the presence of a detected face can be concluded. Our pruning algorithm maximizes the face detection such that a few false positives may be detected, but all faces present are correctly identified. en_US
dc.subject Faculty research day en_US
dc.title Parallel and Distributed Object Recognition en_US
dc.type Presentation en_US
dc.institute.department School of Engineering en_US
dc.institute.name University of Bridgeport en_US
dc.event.name Faculty Research Day en_US

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