Improving behaviour classification consistency: a technique from biological taxonomy

Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. In practice, much of this work will be performed by multiple observers, and maximising inter-observer consistency is of particular importance. Another discipline where consistency in classification is vital is biological taxonomy. A classification tool of great utility, the binary key, is designed to simplify the classification decision process and ensure consistent identification of proper categories. We show how this same decision-making tool - the binary key - can be used to promote consistency in the classification of behaviour. The construction of a binary key also ensures that the categories in which behaviour is classified are complete and non-overlapping. We discuss the general principles of design of binary keys, and illustrate their construction and use with a practical example from education research.

Anisotropy of spin relaxation of water protons in cartilage and tendon

Transverse spin relaxation rates of water protons in articular cartilage and tendon depend on the orientation of the tissue relative to the applied static magnetic field. This complicates the interpretation of magnetic resonance images of these tissues. At the same time, relaxation data can provide information about their organisation and microstructure. We present a theoretical analysis of the anisotropy of spin relaxation of water protons observed in fully hydrated cartilage. We demonstrate that the anisotropy of transverse relaxation is due almost entirely to intramolecular dipolar coupling modulated by a specific mode of slow molecular motion: the diffusion of water molecules in the hydration shell of a collagen fibre around the fibre, such that the molecular director remains perpendicular to the fibre. The theoretical anisotropy arising from this mechanism follows the “magic-angle” dependence observed in magnetic-resonance measurements of cartilage and tendon and is in good agreement with the available experimental results. We discuss the implications of the theoretical findings for MRI of ordered collagenous tissues.

Development of a biaxial compression device for biological samples : preliminary experimental results for a closed cell foam

Biological tissues are subjected to complex loading states in vivo and in order to define constitutive equations that effectively simulate their mechanical behaviour under these loads, it is necessary to obtain data on the tissue's response to multiaxial loading. Single axis and shear testing of biological tissues is often carried out, but biaxial testing is less common. We sought to design and commission a biaxial compression testing device, capable of obtaining repeatable data for biological samples. The apparatus comprised a sealed stainless steel pressure vessel specifically designed such that a state of hydrostatic compression could be created on the test specimen while simultaneously unloading the sample along one axis with an equilibrating tensile pressure. Thus a state of equibiaxial compression was created perpendicular to the long axis of a rectangular sample. For the purpose of calibration and commissioning of the vessel, rectangular samples of closed cell ethylene vinyl acetate (EVA) foam were tested. Each sample was subjected to repeated loading, and nine separate biaxial experiments were carried out to a maximum pressure of 204 kPa (30 psi), with a relaxation time of two hours between them. Calibration testing demonstrated the force applied to the samples had a maximum error of 0.026 N (0.423% of maximum applied force). Under repeated loading, the foam sample demonstrated lower stiffness during the first load cycle. Following this cycle, an increased stiffness, repeatable response was observed with successive loading. While the experimental protocol was developed for EVA foam, preliminary results on this material suggest that this device may be capable of providing test data for biological tissue samples. The load response of the foam was characteristic of closed cell foams, with consolidation during the early loading cycles, then a repeatable load-displacement response upon repeated loading. The repeatability of the test results demonstrated the ability of the test device to provide reproducible test data and the low experimental error in the force demonstrated the reliability of the test data.

Biological performance of a polycaprolactone-based scaffold used as fusion cage device in a large animal model of spinal reconstructive surgery

A bioactive and bioresorbable scaffold fabricated from medical grade poly (epsilon-caprolactone) and incorporating 20% beta-tricalcium phosphate (mPCL–TCP) was recently developed for bone regeneration at load bearing sites. In the present study, we aimed to evaluate bone ingrowth into mPCL–TCP in a large animal model of lumbar interbody fusion. Six pigs underwent a 2-level (L3/4; L5/6) anterior lumbar interbody fusion (ALIF) implanted with mPCL–TCP þ 0.6 mg rhBMP-2 as treatment group while four other pigs implanted with autogenous bone graft served as control. Computed tomographic scanning and histology revealed complete defect bridging in all (100%) specimen from the treatment group as early as 3 months. Histological evidence of continuing bone remodeling and maturation was observed at 6 months. In the control group, only partial bridging was observed at 3 months and only 50% of segments in this group showed complete defect bridging at 6 months. Furthermore, 25% of segments in the control group showed evidence of graft fracture, resorption and pseudoarthrosis. In contrast, no evidence of graft fractures, pseudoarthrosis or foreign body reaction was observed in the treatment group. These results reveal that mPCL–TCP scaffolds could act as bone graft substitutes by providing a suitable environment for bone regeneration in a dynamic load bearing setting such as in a porcine model of interbody spine fusion.

Constraints on the complete optimization of human motion

In sport and exercise biomechanics, forward dynamics analyses or simulations have frequently been used in attempts to establish optimal techniques for performance of a wide range of motor activities. However, the accuracy and validity of these simulations is largely dependent on the complexity of the mathematical model used to represent the neuromusculoskeletal system. It could be argued that complex mathematical models are superior to simple mathematical models as they enable basic mechanical insights to be made and individual-specific optimal movement solutions to be identified. Contrary to some claims in the literature, however, we suggest that it is currently not possible to identify the complete optimal solution for a given motor activity. For a complete optimization of human motion, dynamical systems theory implies that mathematical models must incorporate a much wider range of organismic, environmental and task constraints. These ideas encapsulate why sports medicine specialists need to adopt more individualized clinical assessment procedures in interpreting why performers' movement patterns may differ.

A brush with the real world : the future of inertial motion capture in live performance

3D Motion capture is a medium that plots motion, typically human motion, converting it into a form that can be represented digitally. It is a fast evolving field and recent inertial technology may provide new artistic possibilities for its use in live performance. Although not often used in this context, motion capture has a combination of attributes that can provide unique forms of collaboration with performance arts. The inertial motion capture suit used for this study has orientation sensors placed at strategic points on the body to map body motion. Its portability, real-time performance, ease of use, and its immunity from line-of-sight problems inherent in optical systems suggest it would work well as a live performance technology. Many animation techniques can be used in real-time. This research examines a broad cross-section of these techniques using four practice-led cases to assess the suitability of inertial motion capture to live performance. Although each case explores different visual possibilities, all make use of the performativity of the medium, using either an improvisational format or interactivity among stage, audience and screen that would be difficult to emulate any other way. A real-time environment is not capable of reproducing the depth and sophistication of animation people have come to expect through media. These environments take many hours to render. In time the combination of what can be produced in real-time and the tools available in a 3D environment will no doubt create their own tree of aesthetic directions in live performance. The case study looks at the potential of interactivity that this technology offers.

Abandoned object detection using multi-layer motion detection

Abandoned object detection (AOD) systems are required to run in high traffic situations, with high levels of occlusion. Systems rely on background segmentation techniques to locate abandoned objects, by detecting areas of motion that have stopped. This is often achieved by using a medium term motion detection routine to detect long term changes in the background. When AOD systems are integrated into person tracking system, this often results in two separate motion detectors being used to handle the different requirements. We propose a motion detection system that is capable of detecting medium term motion as well as regular motion. Multiple layers of medium term (static) motion can be detected and segmented. We demonstrate the performance of this motion detection system and as part of an abandoned object detection system.

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.