Active cameras provide a navigating vehicle with the ability to fixate and track features over extended periods of time, and wide fields of view. While it is relatively straightforward to apply fixating vision to tactical, short-term navigation tasks, using serial fixation on a succession of features to provide global information for strategic navigation is more involved. However, active vision is seemingly well-suited to this task: the ability to measure features over such a wide range means that the same ones can be used as a robot makes a wide range of movements. This has advantages for map-building and localisation. The core work of this thesis concerns simultaneous localisation and map-building for a robot with a stereo active head, operating in an unknown environment and using point features in the world as visual landmarks. Importance has been attached to producing maps which are useful for extended periods of navigation. Many map-building methods fail on extended runs because ...

This paper demonstrates a method of using nonmetric visual information derived from an uncalibrated active vision system to navigate an autonomous vehicle through free-space regions detected in a cluttered environment. The structure of 3-space is recovered modulo an affine transformation using an uncalibrated active stereo head carried by the vehicle. The plane at infinity, necessary for recovering affine structure from projective structure, is found in a novel manner by making controlled rotations of the head. The structure is composed of 3D points obtained by detecting and matching image corners through the stereo image sequence. Considerable care has been taken to ensure that the processing is reliable, robust and automatic. Driveable regions are determined from the projection of the affine structure onto a plane parallel to the ground determined using projective constructs. Two methods of negotiating the regions are explored. The first introduces metric information to allow contro...

Traffic statistics desired by road engineers and planners, and "traffic warning" systems demand real-time performance which precludes the use of batch processing. We apply recent real-time tracking techniques along with scene specific tuning of the dynamics to enable the tracker to accurately predict target location and thus reduce the amount of search and/or image processing required. The benefits of learning dynamics for accurate prediction are speed -- our tracker operates at frame rate -- and smoothing of vibration. Initial calibration of the projective relationship between the image and ground planes enables metric information to be derived from the image positions and velocities without full camera calibration. Results are presented on real-world traffic scenes showing the tracker to be both fast and robust to vibrations which are inevitable in traffic locations. 1 Introduction and Related Work Automatic surveillance of traffic has been of interest for many years. As early as ...

This paper demonstrates an approach which exploits an active camera as a projective pointing mechanism. The optical centre of a static camera is notionally substituted by the centre of rotation of the active camera, as is the image plane by a frontal plane, a plane perpendicular to the optical axis of the active camera in its resting direction. Algorithms devised for 3D motion and 3D structure recovery using a single passive camera become immediately applicable to the active camera without need for reformulation. Furthermore, because the active camera can access a panoramic field of view, instabilities which may arise when the field of view is small, or because the shared field of view between successive views after movement is small, are lessened. Two quite different applications of the idea are presented. In the first, the homography between a planar surface in the scene and the frontal plane is recovered and used to recover scene trajectories. In the second, the essential matrix bet...

This paper describes a vision processing architecture which together with a robotic camera platform and control subsystem comprise a multi-processor real-time system for research into active vision. Experimentation in time-critical aspects of the active vision paradigm over several years has demonstrated the flexibility of "pipe-groups" used as the building block in the system. The design of the entire system is overviewed, and the design of pipe-groups and their software is described in more detail. An active method of determining the exact processing latency, required for stable control, is explained. The paper illustrates the use of the pipe-group processing architecture and its real-time processing capabilities with an example of active stereo tracking and structure recovery using the method of affine tranfer.

Abstract—Systems that provide ground movement management at airports, maintaining ground safety and increasing air traffic capacity, are called A-SMGCS (Advanced Surface Movement Guidance and Control Systems). However, common A-SMGCS systems, based on surface movement radars (SMR), are affected by limitations in their coverage due to reflections or shadows from objects on the airport surface. Hence, the use of a complementary system is necessary to act as a “gap-filler”, i.e. to provide accurate ground movement information for these problematic areas. This paper aims to present a novel costeffective video-based system to act as a “gap-filler ” for existing A-SMGCS systems. The proposed system consists of a network of intelligent digital cameras, which are able to detect the presence of an aircraft or vehicle in specific locations within their fields of view, and then provide this information to a Multiple Hypothesis Tracking (MHT) algorithm to extract target tracks. Camera network; image processing; motion detection; air traffic management; tracking I.