Self-calibration of stationary non-rotating zooming cameras

This paper proposes a new method for self-calibrating a set of stationary non-rotating zooming cameras. This is a realistic configuration, usually encountered in surveillance systems, in which each zooming camera is physically attached to a static structure (wall, ceiling, robot, or tripod). In particular, a linear, yet effective method to recover the affine structure of the observed scene from two or more such stationary zooming cameras is presented. The proposed method solely relies on point correspondences across images and no knowledge about the scene is required. Our method exploits the mostly translational displacement of the so-called principal plane of each zooming camera to estimate the location of the plane at infinity. The principal plane of a camera, at any given setting of its zoom, is encoded in its corresponding perspective projection matrix from which it can be easily extracted. As a displacement of the principal plane of a camera under the effect of zooming allows the identification of a pair of parallel planes, each zooming camera can be used to locate a line on the plane at infinity. Hence, two or more such zooming cameras in general positions allow the obtainment of an estimate of the plane at infinity making it possible, under the assumption of zero-skew and/or known aspect ratio, to linearly calculate the camera's parameters. Finally, the parameters of the camera and the coordinates of the plane at infinity are refined through a nonlinear least-squares optimization procedure. The results of our extensive experiments using both simulated and real data are also reported in this paper.     

Simultaneous kinematic calibration,localization, and mapping (SKCLAM) for industrial robot manipulators†

Recently, the demand for more accurate, productive, and economical robot manipulators is increasing in the robotics industry. However, a manipulator will produce kinematic errors during production. Thus low-cost kinematic calibration is demanded. Moreover, environmental mapping is also demanded to plan the motions of the manipulator. In this paper, we proposed a simultaneous kinematic calibration, localization, and mapping (SKCLAM) method, which can simultaneously calibrate the kinematic parameters of an industrial robot manipulator using a commercial RGB-D camera attached to its end effector to reconstruct its surroundings. In our method, the kinematic calibration is achieved with feature detection and epipolor geometry. Synthetic and real data experiments were conducted to verify the SKCLAM method. We succeeded in reducing the kinematic errors of the manipulator and reconstructing dense 3D maps of the workspace in the experiments.     

The impacts of speed cameras on road accidents: An application of propensity score matching methods

This paper aims to evaluate the impacts of speed limit enforcement cameras on reducing road accidents in the UK by accounting for both confounding factors and the selection of proper reference groups. The propensity score matching (PSM) method is employed to do this. A naïve before and after approach and the empirical Bayes (EB) method are compared with the PSM method. A total of 771 sites and 4787 sites for the treatment and the potential reference groups respectively are observed for a period of 9 years in England. Both the PSM and the EB methods show similar results that there are significant reductions in the number of accidents of all severities at speed camera sites. It is suggested that the propensity score can be used as the criteria for selecting the reference group in before-after control studies. Speed cameras were found to be most effective in reducing accidents up to 200 meters from camera sites and no evidence of accident migration was found.     

Spherical approximation for multiple cameras in motion estimation: Its applicability and advantages

Estimating motions of a multi-camera system which may not have overlapping fields of view is generally complex and computationally expensive because of the non-zero offset between each camera’s center. It is conceivable that if we can assume that multiple cameras share a single optical center, and thus can be modeled as a spherical imaging system, motion estimation and calibration of this system would become simpler and more efficient.     

Effect of Space Charge on the Propagation Path of Air Gap Discharge

The existence of space charge may be addressed as one of the reasons that could cause shielding failure of transmission lines. In order to study the effect of s...     

Characterization of low-light-level cameras for digitized video microscopy

The use of low-light-level video cameras and solid-state image detectors in conjunction with image digitizers for optical microscopy is increasing dramatically as more people learn about such systems, and as they become more powerful, less expensive, and easier to use. However, there is currently little information available allowing comparison between cameras, or for determining camera suitability for a given experiment. In this paper, we describe a series of tests designed to characterize the performance of low-light-level cameras. The results of these tests should assist in the selection of appropriate cameras for given video microscopy applications.     

高速智能相机一维条码的自适应快速定位

随着现代科技的高速发展,一些高新领域要求智能相机具备一维条码的高速解读功能,其关键技术是一维条码的自适应快速定位。为了更快速地进行复杂背景和倾斜、破损情况下条码定位,提出了一种应用于智能相机的新方法。该方法的基本原理是基于DSP运算特征的条码形态学特征分析,利用基于DSP的快速区域分析算法得到区域特征,并通过筛选和扫描完成最终的定位。据我们所知,将基于DSP的快速区域分析算法应用于智能相机,为一维条码的高速解读奠定了坚实的技术支撑,在国内还未见报道。     

高速拼接CCD相机时序设计

高速拼接CCD相机是目前我国空间目标监控领域中急需的CCD相机之一,相机的研制对提高我国高速拼接CCD相机的研制能力有很大的推动作用。本文重点介绍了16通道高速拼接CCD相机的时序设计,以及相机的实测结果,并对相机的实际应用前景进行了展望。     

图像拼接技术在双摄像机监控中的应用

针对单摄像机监控范围的局限性,给出一种双摄像机图像拼接方法。首先检测出视频序列图像的兴趣点,并引入改进的尺度不变特征变换算法构建64维匹配描述子;在匹配过程,采用BBF算法进行匹配,提高搜索效率;匹配完成后,采用随机抽样一致性消除误匹配;最后采用加权平均法进行视频序列图像融合,实现序列图像的无缝拼接。实验结果表明,本文方法有较高的匹配效率和匹配准确率,可以明显扩大视频监控的范围,其在视频监控、信息收集及司法取证等方面有一定的实际应用价值。     

A flexible architecture for multi-view 3DTV based on uncalibrated cameras

This paper presents a novel flexible architecture for 3DTV based on multiple uncalibrated cameras. The proposed signal representation improves the interactivity of dense point-based methods, making them appropriate for modeling the scene semantics and free-viewpoint 3DTV applications. The main concern is to address the shortcomings of depth image-based 3D video systems for free-viewpoint visualization, and to provide an efficient implementation of the rendering part which is computationally intensive as well potentially determine the view quality. Novel rendering algorithms are added that specifically aim at solving the rendering artifacts, and sampling issues encountered in wide baseline extensions and arbitrary camera movements. To optimize the process, a “selective” warping technique is proposed that takes the advantage of temporal coherence to reduce the computational overhead. Performance is illustrated on challenging videos to prove the suitability and flexibility of the architecture for advanced 3DTV systems.