60th Annual Report on Research 2015

In the past academic year, one physics major at Saint Peter’s University worked on this project with the collaboration from Beihang University. This effort include two projects that will be reported as follows.

1) A 3D infrared imaging method based on binocular stereo vision

Currently, the research on infrared thermography is mainly focused on 2D images, lacking the information in depth orientation. However, it is necessary and important to put 3D infrared thermography into consideration. A 3D infrared imaging system can be obtained by combining 3D imaging technique with infrared thermography. The characteristics of the two kinds of techniques are fused and the range of application can be broadened.

In this project, a novel 3D infrared imaging method based on binocular stereo vision is designed. An infrared camera is integrated to the binocular stereo vision system, and the 3D shape and the infrared information are fused to obtain the 3D infrared image.

The system is mainly composed of two visible-light cameras and an infrared camera. The registration of the corresponding points in different images is accomplished based on trifocal tensor and gray level interpolation. The method effectively combines binocular stereo vision technique and infrared thermography. The system designed is featured as non-contact and high-precision, and exhibits 3D temperature information at the same time, providing technical reference in industrial monitoring, temperature detecting, medical diagnosis and other applications. Two sets of experiment were carried out using this method, and the experiments demonstrated good results in the registration of 3D metric information and 2D infrared image, as well as dealing with the difference in camera resolution. The system showed fine overall performance in 3D infrared imaging.

The system offers only the relative temperature relationship in different parts of the object. The temperature calibration is required in order to obtain the exact temperature. Besides, there’s still no adequate evaluation criterion for the results of the 3D infrared imaging. Future work is to be focused on these aspects.

2) Global Calibration of Multiple Cameras Based on Sphere Targets

Global calibration method for multi-camera system is critical to the accuracy of vision measurement. Such a method based on several groups of sphere targets and a precision auxiliary camera is designed in this project. Each camera to be calibrated observes a group (at least three) of spheres, while the auxiliary camera observes all the spheres. The global calibration can be achieved after each camera reconstructs the sphere centers in its field of view. In the process of reconstructing a sphere center, a parameter equation is used to describe the sphere projection model. Theoretical analysis and computer simulation are carried out to analyze the factors that affect the calibration accuracy. Simulation results show that the parameter equation can largely improve the reconstruction accuracy. In the experiments, a two-camera system calibrated by our method is used to measure a distance about 578mm, and the root mean squared error is within 0.14mm. Furthermore, the experiments indicate that the method has simple operation and good flexibility, especially for the onsite multiple cameras without common field of view.

A new global calibration method is developed. In the calibration process, an isotropic sphere target can be simultaneously observed by different cameras from different directions, so the blind zones are reduced. There is no restriction on the position relationship between any two spheres, so the method is flexible in complex on-site environment. Moreover, a one-time operation can globally calibrate all the cameras without common FOV. It avoids the heavy workloads and accuracy loss caused by other repeated operations. Parameter equation is also used to fit the ellipse curve to improve the global calibration accuracy. Our experiments show that the proposed method has the advantages of simple operation, high accuracy and good flexibility. It can conveniently realize the global calibration of complexly distributed cameras without common FOV. In the practical application of this method, images with high-quality ellipse contours are necessary to the high accuracy of calibration.