Automatic registration of laser reflectance and colour intensity images for 3D reconstruction

The objective of the work presented in this paper is to generate complete, high-resolution models of real world scenes from passive intensity images and active range sensors. In previous work, an automatic method has been developed in order to compute 3D models of real world scenes from laser range data. The aim of this project is to improve these existing models by fusing range and intensity data. The paper presents different techniques in order to find correspondences between the different sets of data. Based on these control points, a robust camera calibration is computed with a minimal user intervention in order to avoid the fastidious point and click phase that is still necessary in many systems. The intensity images are then re-projected into the laser coordinate frame to produce an image that combines the laser reflectance and the available video intensity images into a colour texture map.     

A machine vision system for enhancing the teleoperation of an industrial robot

This paper describes a real-time vision system that enhances the teleoperation of a servicing tool used in the heat exchangers of nuclear power plants. The vision system is used to track the position of the tool as it moves over a sheet of tube ends. A map-based strategy is adopted for the estimation of the position. The system incorporates a novel method for a foreshortening correction that is applied prior to map referencing. A hypothesize and verify scheme locates two image features that correspond to two map features. An efficient scheme for extracting image features is developed to locate these two features (tube-end centers) in the image. Two different types of heat-exchanger tube sheets are accounted for. They are those with tube ends placed in a square grid and those with tube ends placed in a triangular grid. The map-based strategy minimizes the cumulative errors in the estimate of the tool head position. The resulting low-cost system has been tested on synthetic and real data. Performance results are given.     

Towards the recovery of extrinsic camera parameters from video records of sewer surveys

The aim of the work reported here is the recovery, from a single image taken inside a roughly cylindrical brick sewer pipe of diameter up to one meter, of the pose of the camera relative to the central axis of the pipe. It is shown that the vanishing point associated with the longitudinal mortar lines carries valuable information about the pose. A method for the automatic detection of this point is presented and used to analyse the camera rotations underlying a number of sewer survey videos. It is similarly shown how the angles between the images of the longitudinal lines can be used to recover information about camera pose. The techniques might form an active part of a more comprehensive image understanding system recovering the three-dimensional shape of a surveyed pipe from survey videos and/or be used as an experimental tool during the design of such a system. Received: 24 June 1997 / Accepted: 17 March 1998     

Camera calibration for a mobile robot prototype

Stereovision is an effective technique to use a CCD video camera to determine the 3D position of a target object from two or more simultaneous views of the scene. Camera calibration is a central issue in finding the position of objects in a stereovision system. This is usually carried out by calibrating each camera independently, and then applying a geometric transformation of the external parameters to find the geometry of the stereo setting. After calibration, the distance of various target objects in the scene can be calculated with CCD video cameras, and recovering the 3D structure from 2D images becomes simpler. However, the process of camera calibration is complicated. Based on the ideal pinhole model of a camera, we describe formulas to calculate intrinsic parameters that specify the correct camera characteristics, and extrinsic parameters that describe the spatial relationship between the camera and the world coordinate system. A simple camera calibration method for our CCD video cameras and corresponding experiment results are also given. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

Person tracking and reidentification: Introducing Panoramic Appearance Map (PAM) for feature representation

This paper develops a concept of Panoramic Appearance Map (PAM) for performing person reidentification in a multi-camera setup. Each person is tracked in multiple cameras and the position on the floor plan is determined using triangulation. Using the geometry of the cameras and the person location, a panoramic map centered at the person’s location is created with the horizontal axis representing the azimuth angle and vertical axis representing the height. Each pixel in the map image gets color information from the cameras which can observe it. The maps between different tracks are compared using a distance measure based on weighted SSD in order to select the best match. Temporalintegration by registering multiple maps over the tracking period improves the matching performance. Experimental results of matching persons between two camera sets show the effectiveness of the approach. This work has been sponsored by the Technical Support Working Group (TSWG) of US Department of Defence (DoD).     

基于参数分离机器人手眼视觉标定方法研究

提出一种简单，快速、不需要标定摄像机内外部参数的标定方法。详细推导了机器人平面手眼视觉系统变换关系，完成了从视觉平面坐标系到机器人参考坐标系的坐标变换。通过参数分离简化求解过程，实践表明这种方法求解速度快、精度高。     

An efficient camera calibration and optimisation method based on orthogonal vanishing points

A more efficient camera calibration and optimisation method based on orthogonal vanishing points is proposed. After extracting corner points on the calibration images by using the Harris algorithm, some parallel lines are fitted via the least square method. The Levenberg–Marquard (L–M) algorithm is used to find out the optimum vanishing points. The intrinsic parameters are solved on the basis of the orthogonal vanishing point characters. The enhanced Tsai’s method is designed to solve the extrinsic parameters. The minimum residue optimisation function is introduced to calculate the distortion coefficients and optimise all parameters globally. The feasibility and efficiency of the proposed method is illustrated by an experimental study. The method can be used to obtain high precision calibration parameters without the need of sophisticated mechanical devices. It has great potential to calibration cameras in the field of computer vision, 3D measurement, etc.     

Multi-Camera Human Activity Monitoring

With the proliferation of security cameras, the approach taken to monitoring and placement of these cameras is critical. This paper presents original work in the area of multiple camera human activity monitoring. First, a system is presented that tracks pedestrians across a scene of interest and recognizes a set of human activities. Next, a framework is developed for the placement of multiple cameras to observe a scene. This framework was originally used in a limited X, Y, pan formulation but is extended to include height (Z) and tilt. Finally, an active dual-camera system for task recognition at multiple resolutions is developed and tested. All of these systems are tested under real-world conditions, and are shown to produce usable results. This work has been supported by the NSF through grants #IIS-0219863, #CNS-0224363, #CNS-0324864, #IIP-0443945, #CNS-0420836, #IIP-0726109, and #CNS-0708344.     

基于UG的摄像头夹子注塑模设计

在分析塑料成型工艺和产品结构特点的基础上,基于UGNX7.0的MoldWizard模块,对摄像头夹子注塑模具的设计过程进行了详细的阐述。与传统的注塑模设计相比,应用UGNX7.0的MoldWizard模块进行注塑模设计,可以大大缩短产品研发周期、模具设计周期和加工周期,有效保证注塑模设计的准确性,提高设计效率,降低成本。该模具设计采用潜伏式浇口保证了塑件的表面质量,采用弹簧复位防止合模时与侧滑块产生干涉。     

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.