A Real-Time Distance Prediction via Deep Learning and Microsoft Kinect

Abstract

3D(Dimension) understanding has become the herald of computer vision and graphics research in the era of technology. It benefits many applications such as autonomous cars, robotics, and medical image processing. The pros and cons of 3D detection bring convenience to the human community instead of 2D detection. The 3D detection consists of RGB (Red, Green and Blue) colour images and depth images which are able to perform better than 2D in real. The current technology is relying on the high costing light detection and ranging (LiDAR). However, the use of Microsoft Kinect has replaced the LiDAR systems for 3D detection gradually. In this project, a Kinect camera is used to extract the depth of image information. From the depth images, the distance can be defined easily. As in the colour scale, the red colour is the nearest and the blue colour is the farthest. The depth image will turn black when reaching the limitation of the Kinect camera measuring range. The depth information collected will be trained with deep learning architecture to perform a real-time distance prediction.