3D Monitoring of Car Surrounds Using Multiple KINECT Devices

• Main Authors: Huang, Hao-Che, 黃浩哲
• Other Authors: 蔡文祥
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/96482730375838513617

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 101 === ABSTRACT In this study, several methods are proposed for 3D monitoring of car surrounds using multiple KINECT devices affixed around a video surveillance vehicle. Around-car object models are constructed with 3D sensing techniques provided by KINECT devices. Based on the constructed models, an around-car monitoring system for car-accident warning and avoidance is developed. Firstly, a method for coordinate conversion based on the pinhole camera model is proposed, which converts the coordinates of the depth image into 3D space points. The method is then used to construct 3D images from the color and depth images acquired with KINECT devices. Also, a geometric correction scheme is employed to correct the bending phenomenon of constructed 3D images. Next, a method for KINECT device calibration using the iterative closest point (ICP) algorithm is proposed, which is used to stitch the 3D images corresponding to the around-car KINECT devices into an around-car 3D image. And by the use of the 3D DWC measure which is an extension of the 2D DWC, the displacements between the 3D images of neighboring KINECT devices are computed, by which a more complete by-passing car model can be constructed and car-accident scenes can be restored. Furthermore, a method for monitoring and computing parameters related to ramps and height-restricting barriers is proposed, which uses trigonometric functions and mathematical geometry to measure the slopes of ramps and calculate the height difference between the car roof and the barrier for pre-warning of possible car collisions. Finally, in order to increase driving safety, a method for predicting the possible direction and movement of the opposite car is proposed. Good experimental results are also shown, which prove the feasibility of the proposed methods for real applications.