Accurate Feature Extraction and Control Point Correction for Camera Calibration with a Mono-Plane Target

The paper addresses two problems related to 3D camera calibration using a single mono-plane calibration target with circular control marks. The first problem is how to compute accurately the locations of the features (ellipses) in images of the target. Since the structure of the control marks is known beforehand, we propose to use a shape-specific searching technique to find the optimal locations of the features. Our experiments have shown this technique generates more accurate feature locations than the state-of-the-art ellipse extraction methods. The second problem is how to refine the control mark locations with unknown manufacturing errors. We demonstrate in a case study, where the control marks are laser printed on a A4 paper, that the manufacturing errors of the control marks can be compensated to a good extent so that the remaining calibration errors are reduced significantly. 1

Tracking a table tennis ball for umpiring purposes

This study investigates tracking a table-tennis ball rapidly from video captured using low-cost equipment for umpiring purposes. A number of highly efficient algorithms have been developed for this purpose. The proposed system was tested using sequences capture from real match scenes. The preliminary results of experiments show that accurate and rapid tracking can be achieved even under challenging conditions, including occlusion and colour merging. This work can contribute to the development of an automatic umpiring system and also has the potential to provide amateur users open access to a detection tool for fast-moving, small, round objects

Kinect Range Sensing: Structured-Light versus Time-of-Flight Kinect

Recently, the new Kinect One has been issued by Microsoft, providing the next generation of real-time range sensing devices based on the Time-of-Flight (ToF) principle. As the first Kinect version was using a structured light approach, one would expect various differences in the characteristics of the range data delivered by both devices. This paper presents a detailed and in-depth comparison between both devices. In order to conduct the comparison, we propose a framework of seven different experimental setups, which is a generic basis for evaluating range cameras such as Kinect. The experiments have been designed with the goal to capture individual effects of the Kinect devices as isolatedly as possible and in a way, that they can also be adopted, in order to apply them to any other range sensing device. The overall goal of this paper is to provide a solid insight into the pros and cons of either device. Thus, scientists that are interested in using Kinect range sensing cameras in their specific application scenario can directly assess the expected, specific benefits and potential problem of either device.Comment: 58 pages, 23 figures. Accepted for publication in Computer Vision and Image Understanding (CVIU