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It is challenging to recognize dynamic three-dimensional (3D) objects in a scattered construction work environment because it is difficult to process large amounts of incomplete and complex site data from optical sensors in real time or near-real time. This paper proposes a model-based automatic dynamic object recognition and registration method, projection-recognition-projection (PRP), to help heavy equipment operators rapidly perceive the 3D working environment at construction sites. In this study, machine vision and laser scanning technologies were used to rapidly recognize and register dynamic target objects in 3D space. The proposed PRP method extracts a target object’s point cloud data from the background scene to significantly reduce scan data size and modeling time. The target objects’ point clouds are then processed to rapidly recognize and register 3D target models from a model database to the corresponding point clouds. Several field tests at construction equipment operation sites show that the proposed PRP framework is promising and can effectively assist heavy construction equipment operations and automated equipment control by rapidly modeling dynamic target objects in 3D views.
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Cho et al. (2013) studied this question.
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