RGB-D Based Desk Object Modelling and Search
Date Issued
2015
Date
2015
Author(s)
Lu, Kung-Hung
Abstract
FINDING desk objects could be annoying with a messy desk. Many previous works used object recognition technique to deal with this object searching problem. However, it usually requires massive pre-training process, which has much more effort when it is transferred to another scenario. In this work, we propose a simple yet effective approach to accomplish desk object modelling and search using a static RGB-D camera. Assume that the desk could be monitored over time, the concept of scene stability is proposed to distinguish between stable and dynamic scene. Object segmentation and modelling are done concurrently by differentiating the current stable scene state and the model of object in database so the new object; while multiple objects tracking is adopted to find the locations of objects in dynamic scene. A user interface is designed in which both locations and appearances of the modelled objects are provided. It is easy for the user to have an understanding of the objects on the desk and the minimum effort is required to find a specific object. A variety of the desk objects with different sizes and thickness are tested, even the objects with indistinguishable volume. We also test the proposed approach for various manipulations. The experimental results demonstrate the feasibility and effectiveness of the proposed desk object modelling and search system.
Subjects
RGB-D video
Segmentation
Multi-Object Tracking
Type
thesis
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