Object Identification Based on 3D Spatial Models of Construction Sites
by Seokho Chi, (Ph.D. Candidate, Dept. of Civil, Architectural and Environmental Engineering, Univ. of Texas at Austin, TX 78712 E-mail: shchi@mail.utexas.edu), Carlos Caldas, (Assistant Professor, Dept. of Civil, Architectural and Environmental Engineering, Univ. of Texas at Austin, TX 78712 E-mail: caldas@mail.utexas.edu), and Dae Young Kim, (Ph.D. Candidate, Dept. of Civil, Architectural and Environmental Engineering, Univ. of Texas at Austin, TX 78712 E-mail: danny77arch@mail.utexas.edu)
pp. 729-736, (doi: http://dx.doi.org/10.1061/40937(261)87)
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| Document type: |
Conference Proceeding Paper |
| Part of: |
Computing in Civil Engineering (2007) |
| Abstract: |
On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene. |
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