Keiichi Yamamoto

Vehicle Lateral Position Estimation Method Based on Matching of Top-View Images

In this paper, a method to estimate the lateral position of the vehicle from a sequence of moving camera images is proposed. Proposed method relies on the plane projective transform (homography) between the ground and the image plane of the present and the next frame. Homographies are obtained according to the information of the calibrated camera and the vehicles speed. The movement of the camera is obtained by the registration of the 2 consecutive input images. The proposed method does not rely on extraction of features such as lines, flow vectors or lane markers, but based on matching of warped top-view images between two consecutive frames. Therefore, vehicle movement can be estimated even from images without such explicit image features or without special sensors or GPS. In this paper, experiments are done with both synthesized and real images and enough accuracy is shown even compared to conventional method

An omnidirectional vision system for bus safety surveillance

Sudden brake seems to be unavoidable in driving practice to prevent from accidence. The sudden brake may often cause falling risks to on-board passengers in public transport and even threaten the lives of the senior. Thus, this paper presents an omnidirectional vision system to assist bus drivers in ensuring the safety for passengers. To this end, we configure an auxiliary camera in the boarding gate to recognize the age of passengers and an omnidirectional camera on the ceiling of the bus to detect and track the passengers. Their trajectories and positions are mapped into a bus layout, together with their age information transferred from the auxiliary camera. This bus layout is shown on a small display in front of bus drivers. Instead of looking to the mirror to guess and gather information of passengers, the driver can collect such necessary information for safe driving. We set up experiments on a real bus and demonstrate the system by preliminary results.

Camera position estimation method based on matching of Top-View images for running vehicle

In this paper, a method which estimates the trajectory of the vehicle from a single vehicle camera is proposed. The proposed method is a model based method which assumes that the vehicle is running on a planar road. The input image is converted to a Top-View image and a matching (registration) between the next Top-View image is done. The registration is done based on an assumed velocity parameter, and repeated with entire candidate parameters. In this paper, a simple model and the particle filter is introduced to decrease the computation cost. Simple model gives a constraint to the registration of the Top-View images, and the particle filter decreases the number of the candidate parameters. Position of the camera is obtained by accumulating the velocity parameters. Experiments shows 3 results. Enough decreasement of the computation cost, suitable estimated trajectory and small enough computation cost to estimate the trajectory of the vehicle.