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- W2346728558 abstract "In this paper, we focus on how to calibrate multi-cameras easily and how to efficiently detect quad-copters with small-numbered particles. Each particle is a six dimensional vector that is composed of 3D position and 3D orientation of a quad-copter in the space. Due to curse of dimensionality, that leads to explosive computational costs with a large amount of high-dimensioned particles. To detect efficiently, we need to put more particles in very promising spaces and few particles in other spaces. Though computational cost is lowered by minimizing particles, in order to track a quad-copter with multiple cameras in real-time, multiple images from the cameras should be synchronized and analyzed. Therefore, lots of the computations still need to be done. Because of this, GPGPU(General-Purpose computing on Graphics Processing Units) is implemented for parallel computing. This method has been successfully tested and gives accurate results in practical situations." @default.
- W2346728558 created "2016-06-24" @default.
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- W2346728558 date "2013-06-30" @default.
- W2346728558 modified "2023-09-24" @default.
- W2346728558 title "Real-Time Quad-Copter Tracking With Multi-Cameras and Ray-based Importance Sampling" @default.
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- W2346728558 doi "https://doi.org/10.13067/jkiecs.2013.8.6.899" @default.
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