Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic-based switching and tuning

This paper presents a novel intelligent multiple-controller framework incorporating a fuzzy-logic-based switching and tuning supervisor along with a generalised learning model (GLM) for an autonomous cruise control application. The proposed methodology combines the benefits of a conventional proportional-integral-derivative (PID) controller, and a PID structure-based (simultaneous) zero and pole placement controller. The switching decision between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using a fuzzy-logic-based supervisor, operating at the highest level of the system. The supervisor is also employed to adaptively tune the parameters of the multiple controllers in order to achieve the desired closed-loop system performance. The intelligent multiple-controller framework is applied to the autonomous cruise control problem in order to maintain a desired vehicle speed by controlling the throttle plate angle in an electronic throttle control (ETC) system. Sample simulation results using a validated nonlinear vehicle model are used to demonstrate the effectiveness of the multiple-controller with respect to adaptively tracking the desired vehicle speed changes and achieving the desired speed of response, whilst penalising excessive control action. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

Eye gaze in virtual environments: evaluating the need and initial work on implementation

For efficient collaboration between participants, eye gaze is seen as being critical for interaction. Video conferencing either does not attempt to support eye gaze (e.g. AcessGrid) or only approximates it in round table conditions (e.g. life size telepresence). Immersive collaborative virtual environments represent remote participants through avatars that follow their tracked movements. By additionally tracking people's eyes and representing their movement on their avatars, the line of gaze can be faithfully reproduced, as opposed to approximated. This paper presents the results of initial work that tested if the focus of gaze could be more accurately gauged if tracked eye movement was added to that of the head of an avatar observed in an immersive VE. An experiment was conducted to assess the difference between user's abilities to judge what objects an avatar is looking at with only head movements being displayed, while the eyes remained static, and with eye gaze and head movement information being displayed. The results from the experiment show that eye gaze is of vital importance to the subjects correctly identifying what a person is looking at in an immersive virtual environment. This is followed by a description of the work that is now being undertaken following the positive results from the experiment. We discuss the integration of an eye tracker more suitable for immersive mobile use and the software and techniques that were developed to integrate the user's real-world eye movements into calibrated eye gaze in an immersive virtual world. This is to be used in the creation of an immersive collaborative virtual environment supporting eye gaze and its ongoing experiments. Copyright (C) 2009 John Wiley & Sons, Ltd.

Robust real-time tracking for visual surveillance

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii) object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright (C) 2007 Hindawi Publishing Corporation. All rights reserved.

The role of spectral- and temporal-envelope room-acoustic cues in auditory selective attention

Listeners can attend to one of several simultaneous messages by tracking one speaker’s voice characteristics. Using differences in the location of sounds in a room, we ask how well cues arising from spatial position compete with these characteristics. Listeners decided which of two simultaneous target words belonged in an attended “context” phrase when it was played simultaneously with a different “distracter” context. Talker difference was in competition with position difference, so the response indicates which cue‐type the listener was tracking. Spatial position was found to override talker difference in dichotic conditions when the talkers are similar (male). The salience of cues associated with differences in sounds, bearings decreased with distance between listener and sources. These cues are more effective binaurally. However, there appear to be other cues that increase in salience with distance between sounds. This increase is more prominent in diotic conditions, indicating that these cues are largely monaural. Distances between spectra calculated using a gammatone filterbank (with ERB‐spaced CFs) of the room’s impulse responses at different locations were computed, and comparison with listeners’ responses suggested some slight monaural loudness cues, but also monaural “timbre” cues arising from the temporal‐ and spectral‐envelope differences in the speech from different locations.

Room-acoustic factors in attentional tracking

In a “busy” auditory environment listeners can selectively attend to one of several simultaneous messages by tracking one listener's voice characteristics. Here we ask how well other cues compete for attention with such characteristics, using variations in the spatial position of sound sources in a (virtual) seminar room. Listeners decided which of two simultaneous target words belonged in an attended “context” phrase when it was played with a simultaneous “distracter” context that had a different wording. Talker difference was in competition with a position difference, so that the target‐word chosen indicates which cue‐type the listener was tracking. The main findings are that room‐acoustic factors provide some tracking cues, whose salience increases with distance separation. This increase is more prominent in diotic conditions, indicating that these cues are largely monaural. The room‐acoustic factors might therefore be the spectral‐ and temporal‐envelope effects of reverberation on the timbre of speech. By contrast, the salience of cues associated with differences in sounds' bearings tends to decrease with distance, and these cues are more effective in dichotic conditions. In other conditions, where a distance and a bearing difference cooperate, they can completely override a talker difference at various distances.

Integrating features for man-made target tracking from FLIR image sequence using particle filter

A new man-made target tracking algorithm integrating features from (Forward Looking InfraRed) image sequence is presented based on particle filter. Firstly, a multiscale fractal feature is used to enhance targets in FLIR images. Secondly, the gray space feature is defined by Bhattacharyya distance between intensity histograms of the reference target and a sample target from MFF (Multi-scale Fractal Feature) image. Thirdly, the motion feature is obtained by differencing between two MFF images. Fourthly, a fusion coefficient can be automatically obtained by online feature selection method for features integrating based on fuzzy logic. Finally, a particle filtering framework is developed to fulfill the target tracking. Experimental results have shown that the proposed algorithm can accurately track weak or small man-made target in FLIR images with complicated background. The algorithm is effective, robust and satisfied to real time tracking.

PETS2010 and PETS2009 evaluation of results using individual ground truthed single views

This paper presents the results of the crowd image analysis challenge of the PETS2010 workshop. The evaluation was carried out using a selection of the metrics developed in the Video Analysis and Content Extraction (VACE) program and the CLassification of Events, Activities, and Relationships (CLEAR) consortium. The PETS 2010 evaluation was performed using new ground truthing create from each independant two dimensional view. In addition, the performance of the submissions to the PETS 2009 and Winter-PETS 2009 were evaluated and included in the results. The evaluation highlights the detection and tracking performance of the authors’ systems in areas such as precision, accuracy and robustness.

Application of Gaussian multi-scale representation to feature tracking in meteorological satellite imagery

Gaussian multi-scale representation is a mathematical framework that allows to analyse images at different scales in a consistent manner, and to handle derivatives in a way deeply connected to scale. This paper uses Gaussian multi-scale representation to investigate several aspects of the derivation of atmospheric motion vectors (AMVs) from water vapour imagery. The contribution of different spatial frequencies to the tracking is studied, for a range of tracer sizes, and a number of tracer selection methods are presented and compared, using WV 6.2 images from the geostationary satellite MSG-2.

Mean-tracking clustering algorithm for radial basis function centre selection

Radial basis functions can be combined into a network structure that has several advantages over conventional neural network solutions. However, to operate effectively the number and positions of the basis function centres must be carefully selected. Although no rigorous algorithm exists for this purpose, several heuristic methods have been suggested. In this paper a new method is proposed in which radial basis function centres are selected by the mean-tracking clustering algorithm. The mean-tracking algorithm is compared with k means clustering and it is shown that it achieves significantly better results in terms of radial basis function performance. As well as being computationally simpler, the mean-tracking algorithm in general selects better centre positions, thus providing the radial basis functions with better modelling accuracy

Learning enhanced 3D models for vehicle tracking

This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic object-centred and appearance-based representations in computer vision giving improved hypothesis verification under iconic matching. The "appearance" of a 3D object is learnt using an eigenspace representation obtained as it is tracked through a scene. The feature representation implicitly models the background and the objects observed enabling the segmentation of the objects from the background. The method is shown to enhance model-based tracking, particularly in the presence of clutter and occlusion, and to provide a basis for identification. The unified approach is discussed in the context of the traffic surveillance domain. The approach is demonstrated on real-world image sequences and compared to previous (edge-based) iconic evaluation techniques.

A new approach for the solution of the optimal set-point tracking problem for nonlinear systems

In this paper, a discrete time dynamic integrated system optimisation and parameter estimation algorithm is applied to the solution of the nonlinear tracking optimal control problem. A version of the algorithm with a linear-quadratic model-based problem is developed and implemented in software. The algorithm implemented is tested with simulation examples.

Sea-ice anomalies in the Sea of Okhotsk and the relationship with storm tracks in the Northern Hemisphere during winter

Previous studies have shown that sea-ice in the Sea of Okhotsk can be affected by local storms; in turn, the resultant sea-ice changes can affect the downstream development of storm tracks in the Pacific and possibly dampen a pre-existing North Atlantic Oscillation (NAO) signal in late winter. In this paper, a storm tracking algorithm was applied to the six hourly horizontal winds from the National Centers for Environmental Prediction (NCEP) reanalysis data from 1978(9) to 2007 and output from the atmospheric general circulation model (AGCM) ECHAM5 forced by sea-ice anomalies in the Sea of Okhotsk. The life cycle response of storms to sea-ice anomalies is investigated using various aspects of storm activity—cyclone genesis, lysis, intensity and track density. Results show that, for enhanced positive sea-ice concentrations in the Sea of Okhotsk, there is a decrease in secondary cyclogenesis, a westward shift in cyclolysis and changes in the subtropical jet are seen in the North Pacific. In the Atlantic, a pattern resembling the negative phase of the NAO is observed. This pattern is confirmed by the AGCM ECHAM5 experiments driven with above normal sea-ice anomalies in the Sea of Okhotsk