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dc.contributor.authorAl-Baraa Abdullah Esmail, Al-Wosabi
dc.contributorSchool of Computer and Communication Engineeringen_US
dc.date2023-02
dc.date.accessioned2023-02-23T01:08:57Z
dc.date.available2023-02-23T01:08:57Z
dc.date.issued2015-05
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/77920
dc.descriptionAccess is limited to UniMAP community.en_US
dc.description.abstractReal time object tracking is one important perception task in robotics is tracking objects using a camera. The goal of object tracking is to find an object’s location in consecutive video frames. Object tracking’s many obvious applications include perception and control for autonomous surveillance systems, identifying and neutralizing threats in missile defense, optimizing traffic control systems, and improving human-computer interaction. Many different algorithms have been proposed for object tracking, including mean-shift tracking, optical flow, and feature matching. Each algorithm has strengths in certain environments and weaknesses in others. I so much relished the learning and discovery opportunity afforded by using kalman filter on tracking objects by the sequence of image.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subject.otherImagesen_US
dc.subject.otherObject trackingen_US
dc.subject.otherImage processingen_US
dc.titleTracing of moving object in the sequence of imageen_US
dc.typeOtheren_US
dc.contributor.advisorDr. Said Amirul Anwar Ab. Hamid


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