Segment - based object detection and recognition

dc.contributor	Graduate Program in Electrical and Electronic Engineering.
dc.contributor.advisor	Bozma, H. Işıl.
dc.contributor.author	Erdem, Rabia Gökçe.
dc.date.accessioned	2023-03-16T10:19:29Z
dc.date.available	2023-03-16T10:19:29Z
dc.date.issued	2018.
dc.description.abstract	This thesis is concerned with object detection and recognition in complex scenes. Both are necessary if robots are to be capable of interacting with their surroundings. Object detection is based on color based segmentation. Features of these segments are used in order to detect and recognize objects. A set of SVM model is constructed in the appearance space and object recognition is done based on these models. The proposed approach is evaluated experimentally in varying scenarios.
dc.format.extent	30 cm.
dc.format.pages	xiii, 64 leaves ;
dc.identifier.other	EE 2018 E74
dc.identifier.uri	https://hdl.handle.net/20.500.14908/12932
dc.publisher	Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018.
dc.subject.lcsh	Object-oriented methods (Computer science)
dc.title	Segment - based object detection and recognition

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