5491850
A comparative study of vision-based lateral control strategies for autonomous highway driving
This paper will present the results of a comparative study of a set of vision-based control strategies that have been applied to the problem of steering an autonomous vehicle along a highway. The aim of this work has been to further our understanding of the characteristics of various control laws that could be applied to this problem with a view to making informed design decisions. The control strategies that we explored include a lead lag control law, a full-state linear controller and input-output linearizing control law. Each of these control strategies was implemented and tested on our experimental vehicle, a Honda Accord LX, both with and without a curvature feedforward component.
16474707
Reconstructing Polyhedral Models of Architectural Scenes from Photographs
This paper presents a new image-based modeling method that facilitates the recovery of accurate polyhedral models of architectural scenes. The method is particularly effective because it exploits many of the constraints that are characteristic of architectural scenes. This work is placed in the context of the FaCade project, whose goal is to use images to produce photo-realistic novel views of architectural scenes.
14456844
Exploration strategies for mobile robots
The problem of programming a robot to carry out a systematic exploration of its environment using realistic sensors is considered. The robot is modeled as a single point moving in a two-dimensional configuration space populated with visually opaque and transparent obstacles. The robot is equipped with proximity sensors, a vision-based recognition system, and a method of odometry, all of which have some uncertainty associated with their measurements. By using visually distinctive configurations of features in the world as natural landmarks, a series of local maps is constructed. The geometrical relationships between mutually visible landmarks are used to build a relational map from this collection of local maps. This representation forms the basis for a systematic exploration algorithm. The approach is implemented in simulation, and results are presented.<<ETX>>
3172134
VideoPlus: A Method for Capturing the Structure and Appearance of Immersive Environments
This paper describes an approach to capturing the appearance and structure of immersive environments based on the video imagery obtained with an omnidirectional camera system. The scheme proceeds by recovering the 3D positions of a set of point and line features in the world from image correspondences in a small set of key frames in the image sequence. Once the locations of these features have been recovered the position of the camera during every frame in the sequence can be determined by using these recovered features as fiducials and estimating camera pose based on the location of corresponding image features in each frame. The end result of the procedure is an omnidirectional video sequence where every frame is augmented with its pose with respect to an absolute reference frame and a 3D model of the environment composed of point and line features in the scene.By augmenting the video clip with pose information we provide the viewer with the ability to navigate the image sequence in new and interesting ways. More specifically the user can use the pose information to travel through the video sequence with a trajectory different from the one taken by the original camera operator. This freedom presents the end user with an opportunity to immerse themselves within a remote environment.
1646981
Reconstruction of Linearly Parameterized Models from Single Images with a Camera of Unknown Focal Length
This paper deals with the problem of recovering the dimensions of an object and its pose from a single image acquired with a camera of unknown focal length. It is assumed that the object in question can be modeled as a polyhedron where the coordinates of the vertices can be expressed as a linear function of a dimension vector. The reconstruction program takes as input, a set of correspondences between features in the model and features in the image. From this information, the program determines an appropriate projection model for the camera, the dimensions of the object, its pose relative to the camera and, in the case of perspective projection, the focal length of the camera. This paper describes how the reconstruction problem can be framed as an optimization over a compact set with low dimension (no more than four). This optimization problem can be solved efficiently by coupling standard nonlinear optimization techniques with a multistart method. The result is an efficient, reliable solution system that does not require initial estimates for any of the parameters being estimated.
8867506
Robust vision-based pose control
The problem of controlling the spatial position and orientation of a robotic platform based on the image data obtained from a video camera mounted on that platform is considered. More specifically, we propose control laws that will cause the robot to achieve and maintain a fixed position and orientation with respect to a set of feature points in the scene. We demonstrate analytically that the proposed control scheme is globally convergent even in the presence of large calibration errors in both the intrinsic parameters of the camera and in the extrinsic parameters which relate the frame of reference of the camera to the body frame of the robot platform which is being controlled. Furthermore, no a priori knowledge about the structure of the scene is assumed.
13161464
Macroscopic traffic flow modelling and ramp metering control using Matlab/Simulink
Computer programs to simulate traffic flow offer an opportunity to evaluate new strategies for reducing delays, congestion, fuel consumption and pollution. This paper describes a Statistical Traffic Model or STM, which is based on accepted macro-modelling concepts, such as the conservation of vehicles and the fundamental traffic diagram. In this case, the model is constructed using the well known Matlab/Simulink™ software package, so providing an integrated approach for data processing, graphical presentation of data, control system design and macroscopic simulation in one straightforward to use, widely available environment. To illustrate the methodology, the STM is applied to a section of the M3/M27 Ramp Metering Pilot Scheme in the UK. This Highways Agency sponsored project, based in the Southampton area, utilises traffic lights at the on-ramp entrances to regulate access to the main carriageway of the motorway, in an attempt to maintain flow close to the capacity. The paper utilises the model to help design a locally-coordinated ramp metering algorithm, based on proportional-integral-plus (PIP) control methods. In this manner, the STM proves particularly valuable for the application of multi-objective optimisation techniques in the design of new traffic management systems.
12495173
Interactions Between Learning and Evolution in Simulated Avian Communication
This paper presents a computational framework for studying the influence of learning on the evolution of avian communication. We conducted computer simulations for exploring the effects of different learning strategies on the evolution of bird song. Experimental results show the genetic assimilation of song repertoires as a consequence of interactions between learning and evolution.
11355264
Automatic Model Selection by Modelling the Distribution of Residuals
Many problems in computer vision involve a choice of the most suitable model for a set of data. Typically one wishes to choose a model which best represents the data in a way that generalises to unseen data without overfitting. We propose an algorithm in which the quality of a model match can be determined by calculating how well the distribution of model residuals matches a distribution estimated from the noise on the data. The distribution of residuals has two components - the measurement noise, and the noise caused by the uncertainty in the model parameters. If the model is too complex to be supported by the data, then there will be large uncertainty in the parameters. We demonstrate that the algorithm can be used to select appropriate model complexity in a variety of problems, including polynomial fitting, and selecting the number of modes to match a shape model to noisy data.
8887048
Using a Soft Core in a SoC Design: Experiences with picoJava
Through our experience in synthesis, validation, test, and integration of the picoJava processor core in a system-on-chip (SoC) design we point out the challenges faced and issues to address in efficient reuse of a soft core.
3852636
Automatic extraction of the face identity-subspace
Abstract Facial variation divides into a number of functional subspaces, and variation unique to the ensemble. An improved method of measuring these is presented, within the space defined by an appearance model. Initial estimates of the subspaces (lighting, pose, identity and expression) are obtained by principal components analysis on appropriate groups of faces. A recoding algorithm is applied to image codings to maximise the probability of coding across these non-orthogonal subspaces. Ensemble-specific variation is then removed by measuring the spatial predictability of the eigenvectors excluding those, which are less predictable than the ensemble. These procedures significantly enhance identity recognition for a disjoint test set.