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A Real-Time Vehicular Vision System to Seamlessly See-Through Cars

机译:一个实时车辆视觉系统,无缝透过汽车

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Overtaking accidents typically occur when the rear car intends to overtake the front car with limited visibility. This lack of visual information is often attributed to the occlusion caused by the front vehicle. Indeed, in many situations the front car hides the presence of obstacles, such as pedestrians or other cars. Nowadays, the generalization of digital camera embedded automotives represents a great potential to reduce the number of these deadly accidents. Thus, we propose a novel collaborative cars method which allows a driver to literally see through the front vehicle to assist in overtaking manoeuvres. In the studied scenario, both cars are equipped with cameras (stereo and monocular cameras for the front and the rear cars, respectively) and share data through an appropriated wireless communication system. Our method generates a seamless transparency effect from the rear car viewpoint using tri-focal tensor image synthesis where the poses of the cameras are estimated using a marker-based pose estimation. In this article, we present an efficient framework designed to reduce the quantity of information to be transferred between the vehicles and to achieve real-time performances (15 fps). Furthermore, our system is assessed through multiple experiments in controlled and real conditions.
机译:当后车打算以有限的能见度超过前车时,通常会发生超车事故。这种缺乏视觉信息通常归因于前车辆引起的遮挡。实际上,在许多情况下,前车隐藏了障碍物的存在,例如行人或其他汽车。如今,数码相机嵌入式汽车的泛化代表了减少这些致命事故的数量的巨大潜力。因此,我们提出了一种新颖的协作汽车方法,该方法允许驾驶员通过前车来看,以帮助超越机动。在所学习的场景中,两辆汽车都配备了相机(分别为前车和后车的立体声和单眼摄像机),并通过适当的无线通信系统共享数据。我们的方法使用基于标记的姿态估计来估计相机的姿势,从后网角度从后轿厢观点产生无缝透明度效果。在本文中,我们提出了一个有效的框架,旨在减少在车辆之间传输的信息量并实现实时性能(15 fps)。此外,我们的系统通过对受控和实际条件的多个实验进行评估。

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