Object tracking using multiple motion modalities

This paper presents an object tracking system that utilises a hybrid multi-layer motion segmentation and optical flow algorithm. While many tracking systems seek to combine multiple modalities such as motion and depth or multiple inputs within a fusion system to improve tracking robustness, current systems have avoided the combination of motion and optical flow. This combination allows the use of multiple modes within the object detection stage. Consequently, different categories of objects, within motion or stationary, can be effectively detected utilising either optical flow, static foreground or active foreground information. The proposed system is evaluated using the ETISEO database and evaluation metrics and compared to a baseline system utilising a single mode foreground segmentation technique. Results demonstrate a significant improvement in tracking results can be made through the incorporation of the additional motion information.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

Inertial motion capture and live performance (with a focus on dance)

3D Motion capture is a fast evolving field and recent inertial technology may expand the artistic possibilities for its use in live performance. Inertial motion capture has three attributes that make it suitable for use with live performance; it is portable, easy to use and can operate in real-time. Using four projects, this paper discusses the suitability of inertial motion capture to live performance with a particular emphasis on dance. Dance is an artistic application of human movement and motion capture is the means to record human movement as digital data. As such, dance is clearly a field in which the use of real-time motion capture is likely to become more common, particularly as projected visual effects including real-time video are already often used in dance performances. Understandably, animation generated in real-time using motion capture is not as extensive or as clean as the highly mediated animation used in movies and games, but the quality is still impressive and the ‘liveness’ of the animation has compensating features that offer new ways of communicating with an audience.

Unmanned Aerial Vehicles UAVs attitude, height, motion estimation and control using visual systems

This paper presents an implementation of an aircraft pose and motion estimator using visual systems as the principal sensor for controlling an Unmanned Aerial Vehicle (UAV) or as a redundant system for an Inertial Measure Unit (IMU) and gyros sensors. First, we explore the applications of the unified theory for central catadioptric cameras for attitude and heading estimation, explaining how the skyline is projected on the catadioptric image and how it is segmented and used to calculate the UAV’s attitude. Then we use appearance images to obtain a visual compass, and we calculate the relative rotation and heading of the aerial vehicle. Additionally, we show the use of a stereo system to calculate the aircraft height and to measure the UAV’s motion. Finally, we present a visual tracking system based on Fuzzy controllers working in both a UAV and a camera pan and tilt platform. Every part is tested using the UAV COLIBRI platform to validate the different approaches, which include comparison of the estimated data with the inertial values measured onboard the helicopter platform and the validation of the tracking schemes on real flights.

Accurate silhouette segmentation using motion detection and graph cuts

Acquiring accurate silhouettes has many applications in computer vision. This is usually done through motion detection, or a simple background subtraction under highly controlled environments (i.e. chroma-key backgrounds). Lighting and contrast issues in typical outdoor or office environments make accurate segmentation very difficult in these scenes. In this paper, gradients are used in conjunction with intensity and colour to provide a robust segmentation of motion, after which graph cuts are utilised to refine the segmentation. The results presented using the ETISEO database demonstrate that an improved segmentation is achieved through the combined use of motion detection and graph cuts, particularly in complex scenes.

Comparison of temporal processing and motion perception in emmetropes and myopes

While spatial determinants of emmetropization have been examined extensively in animal models and spatial processing of human myopes has also been studied, there have been few studies investigating temporal aspects of emmetropization and temporal processing in human myopia. The influence of temporal light modulation on eye growth and refractive compensation has been observed in animal models and there is evidence of temporal visual processing deficits in individuals with high myopia or other pathologies. Given this, the aims of this work were to examine the relationships between myopia (i.e. degree of myopia and progression status) and temporal visual performance and to consider any temporal processing deficits in terms of the parallel retinocortical pathways. Three psychophysical studies investigating temporal processing performance were conducted in young adult myopes and non-myopes: (1) backward visual masking, (2) dot motion perception and (3) phantom contour. For each experiment there were approximately 30 young emmetropes, 30 low myopes (myopia less than 5 D) and 30 high myopes (5 to 12 D). In the backward visual masking experiment, myopes were also classified according to their progression status (30 stable myopes and 30 progressing myopes). The first study was based on the observation that the visibility of a target is reduced by a second target, termed the mask, presented quickly after the first target. Myopes were more affected by the mask when the task was biased towards the magnocellular pathway; myopes had a 25% mean reduction in performance compared with emmetropes. However, there was no difference in the effect of the mask when the task was biased towards the parvocellular system. For all test conditions, there was no significant correlation between backward visual masking task performance and either the degree of myopia or myopia progression status. The dot motion perception study measured detection thresholds for the minimum displacement of moving dots, the maximum displacement of moving dots and degree of motion coherence required to correctly determine the direction of motion. The visual processing of these tasks is dominated by the magnocellular pathway. Compared with emmetropes, high myopes had reduced ability to detect the minimum displacement of moving dots for stimuli presented at the fovea (20% higher mean threshold) and possibly at the inferior nasal retina. The minimum displacement threshold was significantly and positively correlated to myopia magnitude and axial length, and significantly and negatively correlated with retinal thickness for the inferior nasal retina. The performance of emmetropes and myopes for all the other dot motion perception tasks were similar. In the phantom contour study, the highest temporal frequency of the flickering phantom pattern at which the contour was visible was determined. Myopes had significantly lower flicker detection limits (21.8 ± 7.1 Hz) than emmetropes (25.6 ± 8.8 Hz) for tasks biased towards the magnocellular pathway for both high (99%) and low (5%) contrast stimuli. There was no difference in flicker limits for a phantom contour task biased towards the parvocellular pathway. For all phantom contour tasks, there was no significant correlation between flicker detection thresholds and magnitude of myopia. Of the psychophysical temporal tasks studied here those primarily involving processing by the magnocellular pathway revealed differences in performance of the refractive error groups. While there are a number of interpretations for this data, this suggests that there may be a temporal processing deficit in some myopes that is selective for the magnocellular system. The minimum displacement dot motion perception task appears the most sensitive test, of those studied, for investigating changes in visual temporal processing in myopia. Data from the visual masking and phantom contour tasks suggest that the alterations to temporal processing occur at an early stage of myopia development. In addition, the link between increased minimum displacement threshold and decreasing retinal thickness suggests that there is a retinal component to the observed modifications in temporal processing.

The silk road project : dance and embodiment in the age of motion capture

The Silk Road Project was a practice-based research project investigating the potential of motion capture technology to inform perceptions of embodiment in dance performance. The project created a multi-disciplinary collaborative performance event using dance performance and real-time motion capture at Deakin University’s Deakin Motion Lab. Several new technological advances in producing real-time motion capture performance were produced, along with a performance event that examined the aesthetic interplay between a dancer’s movement and the precise mappings of its trajectories created by motion capture and real-time motion graphic visualisations.

Reading the play : adaptation by prediction of agent motion

An adaptive agent improves its performance by learning from experience. This paper describes an approach to adaptation based on modelling dynamic elements of the environment in order to make predictions of likely future state. This approach is akin to an elite sports player being able to “read the play”, allowing for decisions to be made based on predictions of likely future outcomes. Modelling of the agent‟s likely future state is performed using Markov Chains and a technique called “Motion and Occupancy Grids”. The experiments in this paper compare the performance of the planning system with and without the use of this predictive model. The results of the study demonstrate a surprising decrease in performance when using the predictions of agent occupancy. The results are derived from statistical analysis of the agent‟s performance in a high fidelity simulation of a world leading real robot soccer team.

Visual motion estimation for an autonomous underwater reef monitoring robot

Performing reliable localisation and navigation within highly unstructured underwater coral reef environments is a difficult task at the best of times. Typical research and commercial underwater vehicles use expensive acoustic positioning and sonar systems which require significant external infrastructure to operate effectively. This paper is focused on the development of a robust vision-based motion estimation technique using low-cost sensors for performing real-time autonomous and untethered environmental monitoring tasks in the Great Barrier Reef without the use of acoustic positioning. The technique is experimentally shown to provide accurate odometry and terrain profile information suitable for input into the vehicle controller to perform a range of environmental monitoring tasks.

Visual motion estimation for an autonomous underwater reef monitoring robot

Performing reliable localisation and navigation within highly unstructured underwater coral reef environments is a difficult task at the best of times. Typical research and commercial underwater vehicles use expensive acoustic positioning and sonar systems which require significant external infrastructure to operate effectively. This paper is focused on the development of a robust vision-based motion estimation technique using low-cost sensors for performing real-time autonomous and untethered environmental monitoring tasks in the Great Barrier Reef without the use of acoustic positioning. The technique is experimentally shown to provide accurate odometry and terrain profile information suitable for input into the vehicle controller to perform a range of environmental monitoring tasks.

Accurate silhouettes for surveillance : improved motion segmentation using graph cuts

Silhouettes are common features used by many applications in computer vision. For many of these algorithms to perform optimally, accurately segmenting the objects of interest from the background to extract the silhouettes is essential. Motion segmentation is a popular technique to segment moving objects from the background, however such algorithms can be prone to poor segmentation, particularly in noisy or low contrast conditions. In this paper, the work of [3] combining motion detection with graph cuts, is extended into two novel implementations that aim to allow greater uncertainty in the output of the motion segmentation, providing a less restricted input to the graph cut algorithm. The proposed algorithms are evaluated on a portion of the ETISEO dataset using hand segmented ground truth data, and an improvement in performance over the motion segmentation alone and the baseline system of [3] is shown.

A world elsewhere : virtual reality, motion capture and early modern theatre

This paper investigates virtual reality representations of the 1599 Boar’s Head Theatre and the Rose Theatre, two renaissance places and spaces. These models become a “world elsewhere” in that they represent virtual recreations of these venues in as much detail as possible. The models are based on accurate archeological and theatre historical records and are easy to navigate particularly for current use. This paper demonstrates the ways in which these models can be instructive for reading theatre today. More importantly we introduce human figures onto the stage via motion capture which allows us to explore the potential between space, actor and environment. This facilitates a new way of thinking about early modern playwrights’ “attitudes to locality and localities large and small”. These venues are thus activated to intersect productively with early modern studies so that the paper can test the historical and contemporary limits of such research.