Efficient object selection using depth and texture information

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.