Self-calibration of wireless cameras with restricted degrees of freedom

This paper presents an approach for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera’s optical center and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. Previous methods for auto-calibration of cameras based on pure rotations fail to work in these two degenerate cases. In addition, our approach includes a modified RANdom SAmple Consensus (RANSAC) algorithm, as well as improved integration of the radial distortion coefficient in the computation of inter-image homographies. We show that these modifications are able to increase the overall efficiency, reliability and accuracy of the homography computation and calibration procedure using both synthetic and real image sequences

Multiple cameras for audio-visual speech recognition in an automotive environment

Audio-visualspeechrecognition, or the combination of visual lip-reading with traditional acoustic speechrecognition, has been previously shown to provide a considerable improvement over acoustic-only approaches in noisy environments, such as that present in an automotive cabin. The research presented in this paper will extend upon the established audio-visualspeechrecognition literature to show that further improvements in speechrecognition accuracy can be obtained when multiple frontal or near-frontal views of a speaker's face are available. A series of visualspeechrecognition experiments using a four-stream visual synchronous hidden Markov model (SHMM) are conducted on the four-camera AVICAR automotiveaudio-visualspeech database. We study the relative contribution between the side and central orientated cameras in improving visualspeechrecognition accuracy. Finally combination of the four visual streams with a single audio stream in a five-stream SHMM demonstrates a relative improvement of over 56% in word recognition accuracy when compared to the acoustic-only approach in the noisiest conditions of the AVICAR database.

Hand-held monocular SLAM in thermal-infrared

Thermal-infrared imagery is relatively robust to many of the failure conditions of visual and laser-based SLAM systems, such as fog, dust and smoke. The ability to use thermal-infrared video for localization is therefore highly appealing for many applications. However, operating in thermal-infrared is beyond the capacity of existing SLAM implementations. This paper presents the first known monocular SLAM system designed and tested for hand-held use in the thermal-infrared modality. The implementation includes a flexible feature detection layer able to achieve robust feature tracking in high-noise, low-texture thermal images. A novel approach for structure initialization is also presented. The system is robust to irregular motion and capable of handling the unique mechanical shutter interruptions common to thermal-infrared cameras. The evaluation demonstrates promising performance of the algorithm in several environments.

Reducing actuator switchings for motion control of autonomous underwater vehicles

A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle and at the same time to minimize a prescribed criterion such as time, energy, payload or combination of those. Indeed, the major issue is that due to the vehicles' design and the actuation modes usually under consideration for underwater platforms the number of actuator switchings must be kept to a small value to ensure feasibility and precision. This constraint is typically not verified by optimal trajectories which might not even be piecewise constants. Our goal is to provide a feasible trajectory that minimizes the number of switchings while maintaining some qualities of the desired trajectory, such as optimality with respect to a given criterion. The one-sided Lipschitz constant is used to derive theoretical estimates. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six degrees-of-freedom and one is minimally actuated with control motions constrained to the vertical plane.

Understanding the relationships between the calf muscle pump, ankle range of motion and healing for adults with venous leg ulcers: a review of the literature

Exercise offers the potential to improve circulation, wound healing outcomes, and functional and emotional wellbeing for adults experiencing venous leg ulceration. Individuals with chronic leg ulcers typically have multiple comorbidities such as arthritis, asthma, chronic obstructive airways disease, cardiac disease or neuromuscular disorders, which would also benefit from regular exercise. The aim of this review is to highlight the relationships between the calf muscle pump and venous return and range of ankle motion for adults with venous leg ulcers. The effect of exercise will also be considered in relation to the healing rates for adults experiencing venous leg ulceration. The findings suggest there is evidence that exercises which engage the calf muscle pump improve venous return. Ankle range of motion, which is crucial for complete activation of the calf muscle pump, can also be improved with simple, home-based exercise programs. However, observational studies still report that venous leg ulcer patients are less physically active than age-matched controls. Therefore, the behavioural reasons for not exercising must be considered. Only two studies, both underpowered, have assessed the effect of exercise on the healing rates of venous leg ulcers. In conclusion, exercise is feasible with this patient population. However, future studies with larger sample sizes are needed to provide stronger evidence to support the therapeutic benefit of exercise as an adjunct therapy in wound care.

Visual motion perception predicts driving hazard perception ability

PURPOSE: To examine the basis of previous findings of an association between indices of driving safety and visual motion sensitivity and to examine whether this association could be explained by low-level changes in visual function. METHODS: 36 visually normal participants (aged 19 – 80 years), completed a battery of standard vision tests including visual acuity, contrast sensitivity and automated visual fields. and two tests of motion perception including sensitivity for movement of a drifting Gabor stimulus, and sensitivity for displacement in a random-dot kinematogram (Dmin). Participants also completed a hazard perception test (HPT) which measured participants’ response times to hazards embedded in video recordings of real world driving which has been shown to be linked to crash risk. RESULTS: Dmin for the random-dot stimulus ranged from -0.88 to -0.12 log minutes of arc, and the minimum drift rate for the Gabor stimulus ranged from 0.01 to 0.35 cycles per second. Both measures of motion sensitivity significantly predicted response times on the HPT. In addition, while the relationship involving the HPT and motion sensitivity for the random-dot kinematogram was partially explained by the other visual function measures, the relationship with sensitivity for detection of the drifting Gabor stimulus remained significant even after controlling for these variables. CONCLUSION: These findings suggest that motion perception plays an important role in the visual perception of driving-relevant hazards independent of other areas of visual function and should be further explored as a predictive test of driving safety. Future research should explore the causes of reduced motion perception in order to develop better interventions to improve road safety.

The effect of warm-up intensity on range of motion and anaerobic performance

Although there is a paucity of scientific support for the benefits of warm-up, athletes commonly warm up prior to activity with the intention of improving performance and reducing the incidence of injuries. The purpose of this study was to examine the role of warm-up intensity on both range of motion (ROM) and anaerobic performance. Nine males (age = 21.7 +/- 1.6 years, height = 1.77 +/- 0.04 m, weight = 80.2 +/- 6.8 kg, and VO2max = 60.4 +/- 5.4 ml/kg/min) completed four trials. Each trial consisted of hip, knee, and ankle ROM evaluation using an electronic inclinometer and an anaerobic capacity test on the treadmill (time to fatigue at 13 km/hr and 20% grade). Subjects underwent no warm-up or a warm-up of 15 minutes running at 60, 70 or 80% VO2max followed by a series of lower limb stretches. Intensity of warm-up had little effect on ROM, since ankle dorsiflexion and hip extension significantly increased in all warm-up conditions, hip flexion significantly increased only after the 80% VO2max warm-up, and knee flexion did not change after any warm-up. Heart rate and body temperature were significantly increased (p < 0.05) prior to anaerobic performance for each of the warm-up conditions, but anaerobic performance improved significantly only after warm-up at 60% VO2max (10%) and 70% VO2max (13%). A 15-minute warm-up at an intensity of 60-70% VO2max is therefore recommended to improve ROM and enhance subsequent anaerobic performance.

Visual sea-floor mapping from low overlap imagery using bi-objective bundle adjustment and constrained motion

In most visual mapping applications suited to Autonomous Underwater Vehicles (AUVs), stereo visual odometry (VO) is rarely utilised as a pose estimator as imagery is typically of very low framerate due to energy conservation and data storage requirements. This adversely affects the robustness of a vision-based pose estimator and its ability to generate a smooth trajectory. This paper presents a novel VO pipeline for low-overlap imagery from an AUV that utilises constrained motion and integrates magnetometer data in a bi-objective bundle adjustment stage to achieve low-drift pose estimates over large trajectories. We analyse the performance of a standard stereo VO algorithm and compare the results to the modified vo algorithm. Results are demonstrated in a virtual environment in addition to low-overlap imagery gathered from an AUV. The modified VO algorithm shows significantly improved pose accuracy and performance over trajectories of more than 300m. In addition, dense 3D meshes generated from the visual odometry pipeline are presented as a qualitative output of the solution.

A picture is worth a thousand words : an approach to learning about visuals

Students in the middle years encounter an increasing range of unfamiliar visuals. Visual literacy, the ability to encode and decode visuals and to think visually, is an expectation of all middle years curriculum areas and an expectation of NAPLAN literacy and numeracy tests. This article presents a multidisciplinary approach to teaching visual literacy that links the content of all learning areas and encourages students to transfer skills from familiar to unfamiliar contexts. It proposes a classification of visuals in six parts: one-dimensional; two-dimensional; map; shape; connection; and picture, based on the properties, rather than the purpose, of the visual. By placing a visual in one of these six categories, students learn to transfer the skills used to decode familiar visuals to unfamiliar cases in the same category. The article also discusses a range of other teaching strategies that can be used to complement this multi-disciplinary approach.

Numerical simulation of red blood cells’ motion : a review

The micro-circulation of blood plays an important role in human body by providing oxygen and nutrients to the cells and removing carbon dioxide and wastes from the cells. This process is greatly affected by the rheological properties of the Red Blood Cells (RBCs). Changes in the rheological properties of the RBCs are caused by certain human diseases such as malaria and sickle cell diseases. Therefore it is important to understand the motion and deformation mechanism of RBCs in order to diagnose and treat this kind of diseases. Although, many methods have been developed to explore the behavior of the RBCs in micro-channels, they could not explain the deformation mechanism of the RBCs properly. Recently developed Particle Methods are employed to explain the RBCs’ behavior in micro-channels more comprehensively. The main objective of this study is to critically analyze the present methods, used to model the RBC behavior in micro-channels, in order to develop a computationally efficient particle based model to describe the complete behavior of the RBCs in micro-channels accurately and comprehensively

Learning hierarchical prototypes of motion time series for interactive systems

Abstract. For interactive systems, recognition, reproduction, and generalization of observed motion data are crucial for successful interaction. In this paper, we present a novel method for analysis of motion data that we refer to as K-OMM-trees. K-OMM-trees combine Ordered Means Models (OMMs) a model-based machine learning approach for time series with an hierarchical analysis technique for very large data sets, the K-tree algorithm. The proposed K-OMM-trees enable unsupervised prototype extraction of motion time series data with hierarchical data representation. After introducing the algorithmic details, we apply the proposed method to a gesture data set that includes substantial inter-class variations. Results from our studies show that K-OMM-trees are able to substantially increase the recognition performance and to learn an inherent data hierarchy with meaningful gesture abstractions.

Re-targeting choreographic enquiry through motion capture

This creative work is the outcome of preliminary experiments through practice aiming to explore the collaboration of a Dancer/choreographer with an Animator, along with enquiry into the intergeneration of motion capture technologies within the work-flow. The animated visuals derived from the motion capture data is not aimed at just re-targeting of movement from one source to another but looks at describing the thought and emotions of the choreographed dance through visual aesthetics.

Efficient articulated trajectory reconstruction using dynamic programming and filters

This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras.

A picture is worth a thousand words : a cross-curricular approach to learning about visuals in STEM

Visuals are a central feature of STEM in all levels of education and many areas of employment. The wide variety of visuals that students are expected to master in STEM prevents an approach that aims to teach students about every type of visual that they may encounter. This paper proposes a pedagogy that can be applied across year levels and learning areas, allowing a school-wide, cross-curricular, approach to teaching about visual, that enhances learning in STEM and all other learning areas. Visuals are classified into six categories based on their properties, unlike traditional methods that classify visuals according to purpose. As visuals in the same category share common properties, students are able to transfer their knowledge from the familiar to unfamiliar in each category. The paper details the classification and proposes some strategies that can be can be incorporated into existing methods of teaching students about visuals in all learning areas. The approach may also assist students to see the connections between the different learning areas within and outside STEM.

Testing the accuracy of luminance maps acquired by smart phone cameras

This paper looks at the accuracy of using the built-in camera of smart phones and free software as an economical way to quantify and analyse light exposure by producing luminance maps from High Dynamic Range (HDR) images. HDR images were captured with an Apple iPhone 4S to capture a wide variation of luminance within an indoor and outdoor scene. The HDR images were then processed using Photosphere software (Ward, 2010.) to produce luminance maps, where individual pixel values were compared with calibrated luminance meter readings. This comparison has shown an average luminance error of ~8% between the HDR image pixel values and luminance meter readings, when the range of luminances in the image is limited to approximately 1,500cd/m2.