1,720,961 research outputs found
First year report
No full textAn autonomous robot surviving in the 3D world may sample its environment as a 2D image sequence, each image differing slightly from its predecessor as a result of robot/scene motion. Furthermore, such a system may not require specific identification of objects within a scene but rather be more "concerned" as to which objects pose a threat or obstacle to some future action, or to the recovery of information about the robot's own motion relative to the scene (the so called ego-motion). This document introduces the concept of 3D environmental structure and sensor motion recovery from 2D image sequences and more especially the concept of an optical flow field. Problems inherent in both sensor and optical flow field characteristics are described and their consequences discussed. By considering the informational content of variously derived flow fields the requirement for 3D environmental structure constraints is introduced. Specific algorithms are classified, detailed and reduced to a canonical format. A parametric noise model is proposed and accuracy bounds derived. Conclusions and further work are presented
Transfer report
No full textThis document has been produced as part of the transfer review process for a part-time internal PhD and describes progress made to date, and the areas of future work in Visual Collision Avoidance. The research aims are the extraction of vehicle specific cues, e.g. tail-lights from filtered monochrome monocular image sequences, and the application of 2D image tracking techniques to obtain estimates of the (relative) 3D vehicle motion(s), e.g. bearing/time-to-contact. The principal application areas are those of collision avoidance, autonomous intelligent cruise control (AICC) and vehicle following for motorway driving. Although the initial application is expected to be at night it is hoped that techniques may also be generalised/developed for application to daytime scenarios. Much of the work described in this document has been performed under the auspices of the EEC Eureka project PROMETHEUS, specifically the PRO-ART collision avoidance demonstrator CED-3. Progress over the last year has been concentrated on region matching and tracking, in order to obtain tracks for trajectory analysis. In addition a system for identifying vehicle-like regions in daylight imagery has been developed
Second year report
No full textThe performance of visible and infrared cameras which can be used for guidance is improving rapidly. These sensor improvements and the increase in computing power now allow image based guidance techniques, such as structure from motion, to be more readily utilised in applications such as intelligent cruise control and convoying. This project seeks to extract vehicle specific cues from image sequences, e.g. red tail-lights, and utilise 2D image plane tracking to obtain estimates for the (relative) 3D vehicle motion, e.g. bearing and time-to-contact. These image based estimates should provide complementary information to other conventional sensors, e.g. millimetric radar, for data fusion. This document is intended to introduce the problems of tracking vehicles in (monochrome filtered) image sequences. A brief review of generic segmentation techniques for extracting vehicle specific cues is presented, together with details of Fourier spectral filtering required to enhance a far infrared image sequence. Details of the specification and acquisition of filtered monochrome image motorway sequences are presented, together with a brief comment on the relationship between filtered monochrome and colour images
Intelligent Collision Avoidance, Control and Guidance
No full textThis paper reviews a variety of advanced signal processing algorithms that have been developed at the University of Southampton as part of the Prometheus (Programme for European traffic flow with highest efficiency and unprecedented safety) programme to achieve an intelligent driver warning system (IDWS). The IDWS includes the detection of road edges, lanes, obstacles and their tracking and identification, estimates of time to collision, and behavioural modelling of drivers for a variety of scenarios. The underlying algorithms are briefly discussed in support of the IDWS
Vehicle Detection and Recognition for Autonomous Intelligent Cruise Control
No full textThe introduction of new technologies such as autonomous intelligent cruise control or collision avoidance schemes to road vehicles necessitates a high degree of robustness and reliability. Whilst very accurate range estimates may be recovered using conventional sensors, e.g. millimetric radar, these typically suffer from both low bearing resolution and potential ambiguities through, for example, false alarms. This work details a novel two-stage vehicle detection and recognition algorithm which combines an image processing area of interest (AOI) designator to cue a secondary recognition process implemented using principal component analysis (PCA) as input to a Multi-Layered Perceptron (MLP) classifier. The combination of an initial detection phase, followed by a recognition process has allowed the classifier design to be greatly simplified. In turn the classifier performance has allowed some of the image processing assumptions to be relaxed, whilst maintaining a high signal to noise ratio (SNR). Both the image processing system and MLP classifier have been designed for real-time implementation and data-fusion with other information sources such as a range/range rate radar
Experience with Optical Flow Algorithms based on the Geometry of Points in Two Frames
No full textA number of optical flow techniques exist for recovering the relative sensor-scene motion from image sequences, for subsequent use in vehicle guidance and navigation tasks. However, the problems of finding depths and motion, as well as various differential and kinematic approximations within the algorithms themselves, often lead to difficulties in the presence of noisy data. We examine various solution means and demonstrate how a small modification to an existing formulation produces a method adequate for our Autonomous Land Vehicle Application
A Mathematical Framework For Robust Obstacle Detection Using Feature Matching
No full textThis paper considers the issues arising from obstacle detection systems for autonomous vehicles, based on image feature matching. The detection probabilities for a 3D obstacle are derived in an algorithm independent framework for a generic vehicle/imaging-sensor model, and subsequently determined for specific scenarios
Vehicle Detection and Recognition in Greyscale Imagery
No full textThis paper details a novel two-stage vehicle detection and recognition algorithm by combining an image-processing region of interest (ROI) designator to cue a secondary recognition process implemented using principal component analysis (PCA) as input to a Multi-Layered Perceptron (MLP) classifier. Both the image-processing system and the MLP classifier have been designed for real-time implementation and data-fusion with other information sources
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
- …
