![]() ![]() Morioka, K., Hashimoto, H.: Appearance based object identification for distributed vision sensors in intelligent space. Shivappa, S., Trivedi, M., Rao, B.: Hierarchical audio-visual cue integration framework for activity analysis in intelligent meeting rooms. IEEE Communications Surveys Tutorials 11(1), 13–32 (2009) Gu, Y., Lo, A., Niemegeers, I.: A survey of indoor positioning systems for wireless personal networks. Odijk, D., Teunissen, P., Zhang, B.: Single-frequency integer ambiguity resolution enabled gps precise point positioning. Kavanagh, B.: Surveying: principles and applications. This process is experimental and the keywords may be updated as the learning algorithm improves. ![]() These keywords were added by machine and not by the authors. The results demonstrate the potentials on feasibility of our method in future construction field. The performance of the algorithm is validated by both synthesized and real data set. Then we detect target object such as pile or pile driver by fast fitting a circle-like geometric model to the data based on Maximum Likelihood Estimation (MLE) inference. To this end, we first develop LRF based surveying system to scan the construction site in real time and gather the 2D laser point data. Over the traditional systems ours is superior to automatically detect the position of the pile or pile driver in real time with high accuracy. The paper confronts this problem by proposing a highly efficient positioning system using a Laser Range Finder (LRF). Real-time positioning a pile for accurate pile driving is desirable for modern construction foundation work, but it suffers from the deficiency of the traditional systems because surveying instruments are manually used to mark the pile positions in which the accuracy heavily depends on the worker’s experience. ![]()
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