Control of a PTZ camera in a hybrid vision system

In this paper, we propose a new approach to steer a PTZ camera in the direction of a detected object visible from another fixed camera equipped with a fisheye lens. This heterogeneous association of two cameras having different characteristics is called a hybrid stereo-vision system. The presented method employs epipolar geometry in a smart way in order to reduce the range of search of the desired region of interest. Furthermore, we proposed a target recognition method designed to cope with the illumination problems, the distortion of the omnidirectional image and the inherent dissimilarity of resolution and color responses between both cameras. Experimental results with synthetic and real images show the robustness of the proposed method

Zoom techniques for achieving scale invariant object tracking in real-time active vision systems

In a surveillance system, a camera operator follows an object of interest by moving the camera, then gains additional information about the object by zooming. As the active vision field advances, the ability to automate such a system is nearing fruition. One hurdle limiting the use of object recognition algorithms in real-time systems is the quality of captured imagery; recognition algorithms often have strict scale and position requirements where if those parameters are not met, the performance rapidly degrades to failure. The ability of an automatic fixation system to capture quality video of an accelerating target is directly related to the response time of the mechanical pan, tilt, and zoom platform—however the price of such a platform rises with its performance. The goal of this work is to create a system that provides scale-invariant tracking using inexpensive off-the-shelf components. Since optical zoom acts as a measurement gain, amplifying both resolution and tracking error, a new second camera with fixed focal length assists the zooming camera if it loses fixation—effectively clipping error. Furthermore, digital zoom adjusts the captured image to ensure position and scale invariance for the higher-level application. The implemented system uses two Sony EVI-D100 cameras on a 2.8GHz Dual Pentium Xeon PC. This work presents experiments to exhibit the effectiveness of the system

Lightfield Analysis and Its Applications in Adaptive Optics and Surveillance Systems

An image can only be as good as the optics of a camera or any other imaging system allows it to be. An imaging system is merely a transformation that takes a 3D world coordinate to a 2D image plane. This can be done through both linear/non-linear transfer functions. Depending on the application at hand it is easier to use some models of imaging systems over the others in certain situations. The most well-known models are the 1) Pinhole model, 2) Thin Lens Model and 3) Thick lens model for optical systems. Using light-field analysis the connection through these different models is described. A novel figure of merit is presented on using one optical model over the other for certain applications. After analyzing these optical systems, their applications in plenoptic cameras for adaptive optics applications are introduced. A new technique to use a plenoptic camera to extract information about a localized distorted planar wave front is described. CODEV simulations conducted in this thesis show that its performance is comparable to those of a Shack-Hartmann sensor and that they can potentially increase the dynamic range of angles that can be extracted assuming a paraxial imaging system. As a final application, a novel dual PTZ-surveillance system to track a target through space is presented. 22X optic zoom lenses on high resolution pan/tilt platforms recalibrate a master-slave relationship based on encoder readouts rather than complicated image processing algorithms for real-time target tracking. As the target moves out of a region of interest in the master camera, it is moved to force the target back into the region of interest. Once the master camera is moved, a precalibrated lookup table is interpolated to compute the relationship between the master/slave cameras. The homography that relates the pixels of the master camera to the pan/tilt settings of the slave camera then continue to follow the planar trajectories of targets as they move through space at high accuracies

A Photogrammetry-Based Hybrid System for Dynamic Tracking and Measurement

Noncontact measurements of lightweight flexible aerospace structures present several challenges. Objects are usually mounted on a test stand because current noncontact measurement techniques require that the net motion of the object be zero. However, it is often desirable to take measurements of the object under operational conditions, and in the case of miniature aerial vehicles (MAVs) and deploying space structures, the test article will undergo significant translational motion. This thesis describes a hybrid noncontact measurement system which will enable measurement of structural kinematics of an object freely moving about a volume. By using a real-time videogrammetry system, a set of pan-tilt-zoom (PTZ) cameras is coordinated to track large-scale net motion and produce high-speed, high-quality images for photogrammetric surface reconstruction. The design of the system is presented in detail. A method of generating the calibration parameters for the PTZ cameras is presented and evaluated and is shown to produce good results. The results of camera synchronization tests and tracking accuracy evaluation are presented as well. Finally, a demonstration of the hybrid system is presented in which all four PTZ cameras track an MAV in flight

Applying Pressure Sensitive Paint Technology to Rotor Blades

This report will present details of a Pressure Sensitive Paint (PSP) system for measuring global surface pressures on rotorcrtaft blades in simulated forward flight at the 14- by 22-Foot Subsonic Tunnel at the NASA Langley Research Center. The basics of the PSP method will be discussed and the modifications that were needed to extend this technology for use on rotor blades. Results from a series of tests will also be presented as well as several areas of improvement that have been identified and are currently being developed for future testing

3D modeling of indoor environments for a robotic security guard

Autonomous mobile robots will play a major role in future security and surveillance tasks for large scale environments such as shopping malls, airports, hospitals and museums. Robotic security guards will autonomously survey such environments, unless a remote human operator takes over control. In this context a 3D model can convey much more useful information than the typical 2D maps used in many robotic applications today, both for visualisation of information and as human machine interface for remote control. This paper addresses the challenge of building such a model of a large environment (50m x 60m) using data from the robot’s own sensors: a 2D laser scanner and a panoramic camera. The data are processed in a pipeline that comprises automatic, semi-automatic and manual stages. The user can interact with the reconstruction process where necessary to ensure robustness and completeness of the model. A hybrid representation, tailored to the application, has been chosen: floors and walls are represented efficiently by textured planes. Non-planar structures like stairs and tables, which are represented by point clouds, can be added if desired. Our methods to extract these structures include: simultaneous localization and mapping in 2D and wall extraction based on laser scanner range data, building textures from multiple omni-directional images using multi-resolution blending, and calculation of 3D geometry by a graph cut stereo technique. Various renderings illustrate the usability of the model for visualising the security guard’s position and environment