Quantifying Submerged Fluvial Topography Using Hyperspatial Resolution UAS Imagery and Structure From Motion Photogrammetry.

Quantifying the topography of rivers and their associated bedforms has been a fundamental concern of fluvial geomorphology for decades. Such data, acquired at high temporal and spatial resolutions, are increasingly in demand for process-oriented investigations of flow hydraulics, sediment dynamics and in-stream habitat. In these riverine environments, the most challenging region for topographic measurement is the wetted, submerged channel. Generally, dry bed topography and submerged bathymetry are measured using different methods and technology. This adds to the costs, logistical challenges and data processing requirements of comprehensive river surveys. However, some technologies are capable of measuring the submerged topography. Through-water photogrammetry and bathymetric LiDAR are capable of reasonably accurate measurements of channel beds in clear water. Whilst the cost of bathymetric LiDAR remains high and its resolution relatively coarse, the recent developments in photogrammetry using Structure from Motion (SfM) algorithms promise a fundamental shift in the accessibility of topographic data for a wide range of settings. Here we present results demonstrating the potential of so called SfM-photogrammetry for quantifying both exposed and submerged fluvial topography at the mesohabitat scale. We show that imagery acquired from a rotary-winged Unmanned Aerial System (UAS) can be processed in order to produce digital elevation models (DEMs) with hyperspatial resolutions (c. 0.02 m) for two different river systems over channel lengths of 50-100 m. Errors in submerged areas range from 0.016 m to 0.089 m, which can be reduced to between 0.008 m and 0.053 m with the application of a simple refraction correction. This work therefore demonstrates the potential of UAS platforms and SfM-photogrammetry as a single technique for surveying fluvial topography at the mesoscale (defined as lengths of channel from c.10 m to a few hundred metres). This article is protected by copyright. All rights reserved.

The Impact of Thought Speed and Variability on Psychological State and Threat Perception: Further Exploration of the Theory of Mental Motion

Thought speed and variability are purportedly common features of specific psychological states, such as mania and anxiety. The present study explored the independent and combinational influence of these variables upon condition-specific symptoms and affective state, as proposed by Pronin and Jacobs’ (Perspect Psychol Sci, 3:461–485, 2008) theory of mental motion. A general population sample was recruited online (N = 263). Participants completed a thought speed and variability manipulation task, inducing a combination of fast/slow and varied/repetitive thought. Change in mania and anxiety symptoms was assessed through direct self-reported symptom levels and indirect, processing bias assessment (threat interpretation). Results indicated that fast and varied thought independently increased self-reported mania symptoms. Affect was significantly less positive and more negative during slow thought. No change in anxiety symptoms or threat interpretation was found between manipulation conditions. No evidence for the proposed combinational influence of speed and variability was found. Implications and avenues for therapeutic intervention are discussed.

A Practical Approach to Using Motion Capture in Performance Dance

Markerless systems are becoming more ubiquitous due to their increased use in video games consoles. Cheap cameras and software suites are making motion capture technologies more freely available to the digitally inclined choreographer. In this workshop we will demonstrate the opportunities and limitations provided by easily accessible and relatively inexpensive markerless motion capture systems. In particular we will explore the capacity of these systems to provide useful data in a live performance scenario where the latency, size and format of the captured data is crucial in allowing real-time processing and visualisation of the captured scene

The effect of smoking nicotine tobacco versus smoking deprivation on motion sickness

BACKGROUND: The experienced smoker maintains adequate nicotine levels by 'puff-by-puff self-control' which also avoids symptomatic nauseating effects of nicotine overdose. It is postulated that there is a varying 'dynamic threshold for nausea' into which motion sickness susceptibility provides an objective toxin-free probe. Hypotheses were that: (i) nicotine promotes motion sickness whereas deprivation protects; and (ii) pleasurable effects of nicotine protect against motion sickness whereas adverse effects of withdrawal have the opposite effect. METHODS: Twenty-six healthy habitual cigarette smokers (mean±SD) 15.3±7.6cigs/day, were exposed to a provocative cross-coupled (coriolis) motion on a turntable, with sequences of 8 head movements every 30s. This continued to the point of moderate nausea. Subjects were tested after either ad-lib normal smoking (SMOKE) or after overnight deprivation (DEPRIV), according to a repeated measures design counter-balanced for order with 1-week interval between tests. RESULTS: Deprivation from recent smoking was confirmed by objective measures: exhaled carbon monoxide CO was lower (P<0.001) for DEPRIV (8.5±5.6ppm) versus SMOKE (16.0±6.3ppm); resting heart rate was lower (P<0.001) for DEPRIV (67.9±8.4bpm) versus SMOKE (74.3±9.5bpm). Mean±SD sequences of head movements tolerated to achieve moderate nausea were more (P=0.014) for DEPRIV (21.3±9.9) versus SMOKE (18.3±8.5). DISCUSSION: Tolerance to motion sickness was aided by short-term smoking deprivation, supporting Hypothesis (i) but not Hypothesis (ii). The effect was was approximately equivalent to half of the effect of an anti-motion sickness drug. Temporary nicotine withdrawal peri-operatively may explain why smokers have reduced risk for postoperative nausea and vomiting (PONV).

Embodied perspective-taking indicated by selective disruption from aberrant self motion

Spatial perspective-taking that involves imagined changes in one’s spatial orientation is facilitated by vestibular stimulation inducing a congruent sensation of self-motion. We examined further the role of vestibular resources in perspective-taking by evaluating whether aberrant and conflicting vestibular stimulation impaired perspective-taking performance. Participants (N = 39) undertook either an “own body transformation” (OBT)task, requiring speeded spatial judgments made from the perspective of a schematic figure, or a control task requiring reconfiguration of spatial mappings from one’s own visuo-spatial perspective. These tasks were performed both without and with vestibular stimulation by whole-body Coriolis motion, according to a repeated measures design, balanced for order. Vestibular stimulation was found to impair performance during the first minute post stimulus relative to the stationary condition. This disruption was task-specific, affecting only the OBT task and not the control task, and dissipated by the second minute post-stimulus. Our experiment thus demonstrates selective temporary impairment of perspective-taking from aberrant vestibular stimulation, implying that uncompromised vestibular resources are necessary for efficient perspective-taking. This finding provides evidence for an embodied mechanism for perspective-taking whereby vestibular input contributes to multisensory processing underlying bodily and social cognition. Ultimately, this knowledge may contribute to the design of interventions that help patients suffering sudden vertigo adapt to the cognitive difficulties caused by aberrant vestibular stimulation.

Compression Efficiency Analysis of Wyner-Ziv Video Coding with Motion Compensated Side Information Interpolation

The Wyner-Ziv video coding (WZVC) rate distortion performance is highly dependent on the quality of the side information, an estimation of the original frame, created at the decoder. This paper, characterizes the WZVC efficiency when motion compensated frame interpolation (MCFI) techniques are used to generate the side information, a difficult problem in WZVC especially because the decoder only has available some reference decoded frames. The proposed WZVC compression efficiency rate model relates the power spectral of the estimation error to the accuracy of the MCFI motion field. Then, some interesting conclusions may be derived related to the impact of the motion field smoothness and the correlation to the true motion trajectories on the compression performance.

A multi-objective approach for the motion planning of redundant manipulators

Kinematic redundancy occurs when a manipulator possesses more degrees of freedom than those required to execute a given task. Several kinematic techniques for redundant manipulators control the gripper through the pseudo-inverse of the Jacobian, but lead to a kind of chaotic inner motion with unpredictable arm configurations. Such algorithms are not easy to adapt to optimization schemes and, moreover, often there are multiple optimization objectives that can conflict between them. Unlike single optimization, where one attempts to find the best solution, in multi-objective optimization there is no single solution that is optimum with respect to all indices. Therefore, trajectory planning of redundant robots remains an important area of research and more efficient optimization algorithms are needed. This paper presents a new technique to solve the inverse kinematics of redundant manipulators, using a multi-objective genetic algorithm. This scheme combines the closed-loop pseudo-inverse method with a multi-objective genetic algorithm to control the joint positions. Simulations for manipulators with three or four rotational joints, considering the optimization of two objectives in a workspace without and with obstacles are developed. The results reveal that it is possible to choose several solutions from the Pareto optimal front according to the importance of each individual objective.

A fractional approach for the motion planning of redundant and hyper-redundant manipulators

The trajectory planning of redundant robots through the pseudoinverse control leads to undesirable drift in the joint space. This paper presents a new technique to solve the inverse kinematics problem of redundant manipulators, which uses a fractional differential of order α to control the joint positions. Two performance measures are defined to examine the strength and weakness of the proposed method. The positional error index measures the precision of the manipulator's end-effector at the target position. The repeatability performance index is adopted to evaluate if the joint positions are repetitive when the manipulator execute repetitive trajectories in the operational workspace. Redundant and hyper-redundant planar manipulators reveal that it is possible to choose in a large range of possible values of α in order to get repetitive trajectories in the joint space.

An evolutionary approach for the motion planning of redundant and hyper-redundant manipulators

The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms are needed. The pseudoinverse control is not repeatable, causing drift in joint space which is undesirable for physical control. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms, leading to an optimization criterion for repeatable control of redundant manipulators, and avoiding the joint angle drift problem. Computer simulations performed based on redundant and hyper-redundant planar manipulators show that, when the end-effector traces a closed path in the workspace, the robot returns to its initial configuration. The solution is repeatable for a workspace with and without obstacles in the sense that, after executing several cycles, the initial and final states of the manipulator are very close.

UAV - based imagery processing using structure from motion and remote sensing technology

With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.

Octopus Standard Automated Perimetry, Pulsar Perimetry, Moorfields Motion Displacement Test and Heidelberg Retinal Tomography in Glaucoma Detection - A Comparison of Diagnostic Accuracy

Purpose: To investigate the accuracy of 4 clinical instruments in the detection of glaucomatous damage. Methods: 102 eyes of 55 test subjects (Age mean = 66.5yrs, range = [39; 89]) underwent Heidelberg Retinal Tomography (HRTIII), (disc area<2.43); and standard automated perimetry (SAP) using Octopus (Dynamic); Pulsar (TOP); and Moorfields Motion Displacement Test (MDT) (ESTA strategy). Eyes were separated into three groups 1) Healthy (H): IOP<21mmHg and healthy discs (clinical examination), 39 subjects, 78 eyes; 2) Glaucoma suspect (GS): Suspicious discs (clinical examination), 12 subjects, 15 eyes; 3) Glaucoma (G): progressive structural or functional loss, 14 subjects, 20 eyes. Clinical diagnostic precision was examined using the cut-off associated with the p<5% normative limit of MD (Octopus/Pulsar), PTD (MDT) and MRA (HRT) analysis. The sensitivity, specificity and accuracy were calculated for each instrument. Results: See table Conclusions: Despite the advantage of defining glaucoma suspects using clinical optic disc examination, the HRT did not yield significantly higher accuracy than functional measures. HRT, MDT and Octopus SAP yielded higher accuracy than Pulsar perimetry, although results did not reach statistical significance. Further studies are required to investigate the structure-function correlations between these instruments.

Towards high-quality simultaneous EEG-fMRI at 7T: Detection and reduction of EEG artifacts due to head motion.

The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.