Robust real-time ground plane motion compensation from a moving vehicle

One method to detect obstacles from a vehicle moving on a planar road surface is the analysis of motion-compensated difference images. In this contribution, a motion compensation algorithm is presented, which computes the required image-warping parameters from an estimate of the relative motion between camera and ground plane. The proposed algorithm estimates the warping parameters from displacements at image corners and image edges. It exploits the estimated confidence of the displacements to cope robustly with outliers. Knowledge about camera calibration, measuremts from odometry, and the previous estimate are used for motion prediction and to stabilize the estimation process when there is not enough information available in the measured image displacements. The motion compensation algorithm has been integrated with modules for obstacle detection and lane tracking. This system has been integrated in experimental vehicles and runs in real time with an overall cycle of 12.5 Hz on low-cost standard hardware. Received: 23 April 1998 / Accepted: 25 August 1999     

Experimenting with nonintrusive motion capture in a virtual environment

A growing number of promising applications requires recognizing human posture and motion. Conventional techniques require us to attach foreign objects to the body, which in some applications is disturbing or even impossible. New, nonintrusive motion capture approaches are called for. The well-known shape-from-silhouette technique for understanding 3D shapes could also be effective for human bodies. We present a novel technique for model-based motion capture that uses silhouettes extracted from multiple views. A 3D reconstruction of the performer can be computed from a silhouette with a technique known as volume intersection. We can recover the posture by fitting a model of the human body to the reconstructed volume. The purpose of this work is to test the effectiveness of this approach in a virtual environment by investigating the precision of the posture and motion obtained with various numbers and arrangements of stationary cameras. An average 1% position error has been obtained with five cameras.     

Creating and retargetting motion by the musculoskeletal human body model

Recently, optimization has been used in various ways to interpolate or retarget human body motions obtained by motion-capturing systems. However, in such cases, the inner structure of a human body has rarely been taken into account, and hence there have been difficulties in simulating physiological effects such as fatigue or injuries. In this paper, we propose a method to create/retarget human body motions using a musculoskeletal human body model. Using our method, it is possible to create dynamically and physiologically feasible motions. Since a muscle model based on Hill's model is included in our system, it is also possible to retarget the original motion by changing muscular parameters. For example, using the muscle fatigue model, a motion where a human body gradually gets tired can be simulated. By increasing the maximal force exertable by the muscles, or decreasing it to zero, training or displacement effects of muscles can also be simulated. Our method can be used for biomechanically correct inverse kinematics, interpolation of motions, and physiological retargetting of the human body motion.     

Robotic hand-eye coordination: new solutions with uncalibrated stereo cameras

This paper presents new and simple solutions to the important problem of robotic hand-eye coordination. Although this problem can be easily solved with precisely calibrated 3D vision system, one question still remains, that is: can this problem be solved with 2D information contained in images without doing any metric measurement with a 3D vision system? Here, we present two new feasible solutions which are both simple (in the sense that a constant mapping matrix is being generated) and practical (in the sense that it works with both simulation and real system).     

Automatic reconstruction of 3D human arm motion from a monocular image sequence

A model-based approach to reconstruction of 3D human arm motion from a monocular image sequence taken under orthographic projection is presented. The reconstruction is divided into two stages. First, a 2D shape model is used to track the arm silhouettes and second-order curves are used to model the arm based on an iteratively reweighted least square method. As a result, 2D stick figures are extracted. In the second stage, the stick figures are backprojected into the scene. 3D postures are reconstructed using the constraints of a 3D kinematic model of the human arm. The motion of the arm is then derived as a transition between the arm postures. Applications of these results are foreseen in the analysis of human motion patterns. Received: 26 January 1996 / Accepted: 17 July 1997     

Motion segmentation and pose recognition with motion history gradients

This paper presents a fast and simple method using a timed motion history image (tMHI) for representing motion from the gradients in successively layered silhouettes. This representation can be used to (a) determine the current pose of the object and (b) segment and measure the motions induced by the object in a video scene. These segmented regions are not “motion blobs”, but instead are motion regions that are naturally connected to parts of the moving object. This method may be used as a very general gesture recognition “toolbox”. We demonstrate the approach with recognition of waving and overhead clapping motions to control a music synthesis program. Accepted: 13 August 2001     

Broadband Cellular Radio Telecommunication Technologies in Distance Learning: A Human Factors Field Study

This paper presents a virtual classroom field experiment utilising broadband cellular radio telecommunication technologies and involving real users. The aim of the investigation was to experiment in the field cellular broadband systems in realising virtual classroom situations. In particular, we investigated learners’ performance and usability aspects of the multimedia tele-education system including ease of use, usefulness, telepresence and users’ satisfaction about the system. Results confirmed the effectiveness of the multimedia system in terms of both technical and psychological features. Some operational results and practical solutions were obtained as well. They included the basic features of multimedia systems used in virtual classroom and the correct procedures for training teachers and learners in the equipment use.     

Trust: Key Elements in Human Supervisory Control Domains

This study aimed to investigate the concept of trust within human supervisory control domains. Using repertory grid methodology, a small homogeneous sample of control engineers from two individual companies within the energy distribution industry were found to share a commonality in what they considered to be important characteristics of trust across three groups: intra-team, inter-team and technology. Sixty constructs were elicited which were reduced to 13 core constructs using content analysis. These were categorised into three separate dimensions; emotive, cognitive and behavioural. Differences were found, both within and between the three groups, according to participants’ scored level of trust for each group. These results are discussed with a view to developing strategies that may enhance trusting behaviours, especially between teams in applied controlled settings.     

Analysis and Classification of Human Driving Behaviour in an Urban Environment*

Intelligent vehicle systems have introduced the need for designers to consider user preferences so as to make several kinds of driving features as driver friendly as possible. This requirement raises the problem of how to suitably analyse human performance so they can be implemented in automatic driving tasks. The framework of the present work is an adaptive cruise control with stop and go features for use in an urban setting. In such a context, one of the main requirements is to be able to tune the control strategy to the driver’s style. In order to do this, a number of different drivers were studied through the statistical analysis of their behaviour while driving. The aim of this analysis is to decide whether it is possible to determine a driver’s behaviour, what signals are suitable for this task and which parameters can be used to describe a driver’s style. An assignment procedure is then introduced in order to classify a driver’s behaviour within the stop and go task being considered. Finally, the findings were analysed subjectively and compared with a statistically objective one.     

Sensorimotor coordination aftereffects of exposure to a virtual environment

Virtual reality environments (VRs) offer unique training opportunities, particularly for training astronauts and preadapting them to microgravity. The purpose of the current research was to compare disturbances in eye–head–hand (EHH) and eye–head (GAZE) sensorimotor coordination produced by repeated exposures to VR systems. In general, we observed significant increases in position errors in manual target acquisition for both horizontal and vertical targets. We also observed a significant decrement in the ability of subjects to maintain gaze on horizontal eccentric targets immediately after exposure to VR. These preliminary findings provide some direction for developing training schedules for VR users that facilitate adaptation and support the idea that VRs may serve as an analog for sensorimotor effects of spaceflight.

Nuclear Reactor Control Room Simulators: Human Factors Research and Development

Simulator studies are powerful means for understanding, designing and managing the complexity of nuclear reactor control if, along with their scenarios, they are correctly designed for that purpose. This contribution to an international state of the art of the use of nuclear reactor control room simulators in human factors research and development summarises the trends and novelties in the theories and methodologies (the reduction of the ambitions of cognitive simulation and the renewal of process-tracing methods, the eclectic search for theoretical and methodological complementarity, the conquests of situation awareness and their limitations, the study of cooperation), in the use of the results (with stress on probabilistic human reliability analysis and design of procedures) and in the construction of simulated situations (with stress on part task simulations and on relations between testing practical and empirical hypotheses and testing theoretical ones).     

A memory-based approach to sensory-motor coordination

In this work a visual-based autonomous system capable of memorizing and recalling sensory-motor associations is presented. The robot's behaviors are based on learned associations between its sensory inputs and its motor actions. Perception is divided into two stages. The first one is functional: algorithmic procedures extract in real time visual features such as disparity and local orientation from the input images. The second stage is mnemonic: the features produced by the different functional areas are integrated with motor information and memorized or recalled. An efficient memory organization and fast information retrieval enables the robot to learn to navigate and to avoid obstacles without need of an internal metric reconstruction of the external environment. Received: 22 November 1996 / Accepted: 18 November 1997     

Motion of disturbances: detection and tracking of multi-body non-rigid motion

We present a new approach to the tracking of very non-rigid patterns of motion, such as water flowing down a stream. The algorithm is based on a “disturbance map”, which is obtained by linearly subtracting the temporal average of the previous frames from the new frame. Every local motion creates a disturbance having the form of a wave, with a “head” at the present position of the motion and a historical “tail” that indicates the previous locations of that motion. These disturbances serve as loci of attraction for “tracking particles” that are scattered throughout the image. The algorithm is very fast and can be performed in real time. We provide excellent tracking results on various complex sequences, using both stabilized and moving cameras, showing a busy ant column, waterfalls, rapids and flowing streams, shoppers in a mall, and cars in a traffic intersection. Received: 24 June 1997 / Accepted: 30 July 1998     

A practical use of cellular neural networks: the stereo-vision problem as an optimisation

A variational way of deriving the relevant parameters of a cellular neural network (CNN) is introduced. The approach exploits the CNN spontaneous internal-energy decrease and is applicable when a given problem can be expressed in terms of an optimisation task. The presented approach is fully mathematical as compared with the typical heuristic search for the correct parameters in the literature on CNNs. This method is practically employed in recovering information on the three-dimensional structure of the environment, through the stereo vision problem. A CNN able to find the conjugate points in a stereogram is fully derived in the proposed framework. Results of computer simulations on several test cases are provided. Received: 1 August 1997 / Accepted: 29 September 1999     

Estimating 3-D rigid body transformations: a comparison of four major algorithms

A common need in machine vision is to compute the 3-D rigid body transformation that aligns two sets of points for which correspondence is known. A comparative analysis is presented here of four popular and efficient algorithms, each of which computes the translational and rotational components of the transform in closed form, as the solution to a least squares formulation of the problem. They differ in terms of the transformation representation used and the mathematical derivation of the solution, using respectively singular value decomposition or eigensystem computation based on the standard representation, and the eigensystem analysis of matrices derived from unit and dual quaternion forms of the transform. This comparison presents both qualitative and quantitative results of several experiments designed to determine (1) the accuracy and robustness of each algorithm in the presence of different levels of noise, (2) the stability with respect to degenerate data sets, and (3) relative computation time of each approach under different conditions. The results indicate that under “ideal” data conditions (no noise) certain distinctions in accuracy and stability can be seen. But for “typical, real-world” noise levels, there is no difference in the robustness of the final solutions (contrary to certain previously published results). Efficiency, in terms of execution time, is found to be highly dependent on the computer system setup.