Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/90095
Title: Efficient object selection using depth and texture information
Authors: Seychell, Dylan
Debono, Carl James
Keywords: Image analysis
Digital images -- Editing
Object-oriented methods (Computer science)
Issue Date: 2016
Publisher: IEEE
Citation: Seychell, D., & Debono, C. J. (2016). Efficient object selection using depth and texture information. In 2016 Visual Communications and Image Processing (VCIP), Chengdu.
Abstract: Object selection is a challenge in computer vision since it is generally a trade-off between accuracy and performance. A popular approach is the use of bounding boxes around objects that are to be selected. Other common techniques provide a set of objects from which the user can then choose. The method presented in this paper is designed around the priority of performance and granular selection of objects in the scene. Experiments performed on a non-parallel implementation of the proposed solution return results in an average time of 0.043s. The technique also returned very good results in the processing of objects that are partially occluded, hence enabling future work in improved identification and recognition of such objects.
URI: https://www.um.edu.mt/library/oar/handle/123456789/90095
Appears in Collections:Scholarly Works - FacICTAI

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