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Vehicle Detection by Sparse Deformable Template Models

机译:稀疏可变形模板模型的车辆检测

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摘要

Vehicle detection is an important problem in computer vision. Several applications including robotics, surveillance and automotive safety are related to vehicle detection. In this paper, we build up a vehicle detection system by combing the active basis model and logistics regression. Active basis model provides a robust and reasonable representation for cars, while logistic regression gives us an efficient classifier for big data. A detailed system framework is presented and some experiments show good performance in both accuracy and speed of the developed system.
机译:车辆检测是计算机视觉中的重要问题。包括机器人技术,监视和汽车安全在内的几种应用与车辆检测有关。本文结合主动基础模型和后勤回归建立了车辆检测系统。主动基础模型为汽车提供了可靠而合理的表示,而逻辑回归为我们提供了大数据的有效分类器。提出了详细的系统框架,并且一些实验显示了所开发系统在准确性和速度上均具有良好的性能。

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