A Predictive Approach to On-line Time Warping of Motion

The paper presents a novel approach to real-time temporal alignment of motion sequences, called On-line Predictive Warping (OPW) and considers potential uses in interactive applications. The approach develops on the methods of aligning motions based on least cost, used in dynamic time warping (DTW), with the short term predictions of smoothing algorithms, in an iterative step through approach. The approach allows a recorded motion sequence to be warped to align it with a users motion as it is being captured. The paper demonstrates the potential feasibility of the approach to support applications in MR and VR, allowing virtual characters to perform and interact with users and live actors in a variety of rehearsal, training, visualisation and performance scenarios

On-line Time Warping of Human Motion Sequences

Some application areas require motions to be time warped on-line as a motion is captured, aligning a partially captured motion to a complete prerecorded motion. For example movement training applications for dance and medical procedures, require on-line time warping for analysing and visually feeding back the accuracy of human motions as they are being performed. Additionally, real-time production techniques such as virtual production, in camera visual effects and the use of avatars in live stage performances, require on-line time warping to align virtual character performances to a live performer. The work in this thesis first addresses a research gap in the measurement of the alignment of two motions, proposing approaches based on rank correlation and evaluating them against existing distance based approaches to measuring motion similarity. The thesis then goes onto propose and evaluate novel methods for on-line time warping, which plot alignments in a forward direction and utilise forecasting and local continuity constraint techniques. Current studies into measuring the similarity of motions focus on distance based metrics for measuring the similarity of the motions to support motion recognition applications, leaving a research gap regarding the effectiveness of similarity metrics bases on correlation and the optimal metrics for measuring the alignment of two motions. This thesis addresses this research gap by comparing the performance of variety of similarity metrics based on distance and correlation, including novel combinations of joint parameterisation and correlation methods. The ability of each metric to measure both the similarity and alignment of two motions is independently assessed. This work provides a detailed evaluation of a variety of different approaches to using correlation within a similarity metric, testing their performance to determine which approach is optimal and comparing their performance against established distance based metrics. The results show that a correlation based metric, in which joints are parameterised using displacement vectors and correlation is measured using Kendall Tau rank correlation, is the optimal approach for measuring the alignment between two motions. The study also showed that similarity metrics based on correlation are better at measuring the alignment of two motions, which is important in motion blending and style transfer applications as well as evaluating the performance of time warping algorithms. It also showed that metrics based on distance are better at measuring the similarity of two motions, which is more relevant to motion recognition and classification applications. A number of approaches to on-line time warping have been proposed within existing research, that are based on plotting an alignment path backwards from a selected end-point within the complete motion. While these approaches work for discrete applications, such as recognising a motion, their lack of monotonic constraint between alignment of each frame, means these approaches do not support applications that require an alignment to be maintained continuously over a number of frames. For example applications involving continuous real-time visualisation, feedback or interaction. To solve this problem, a number of novel on-line time warping algorithms, based on forward plotting, motion forecasting and local continuity constraints are proposed and evaluated by applying them to human motions. Two benchmarks standards for evaluating the performance of on-line time warping algorithms are established, based on UTW time warping and compering the resulting alignment path with that produced by DTW. This work also proposes a novel approach to adapting existing local continuity constraints to a forward plotting approach. The studies within this thesis demonstrates that these time warping approaches are able to produce alignments of sufficient quality to support applications that require an alignment to be maintained continuously. The on-line time warping algorithms proposed in this study can align a previously recorded motion to a user in real-time, as they are performing the same action or an opposing action recorded at the same time as the motion being align. This solution has a variety of potential application areas including: visualisation applications, such as aligning a motion to a live performer to facilitate in camera visual effects or a live stage performance with a virtual avatar; motion feedback applications such as dance training or medical rehabilitation; and interaction applications such as working with Cobots

Recent Advances to Estimation of Fixed-Interface Modal Models Using Dynamic Substructuring

In 2010, Allen & Mayes proposed to estimate the fixed-interface modes of a structure by measuring the modes of the structure bolted to a fixture and then applying constraints to the fixture using the transmission simulator method. While the method proved useful, and has indeed been used in studies since that point, a few peculiarities were noted. First, in some cases the estimated fixed-base natural frequencies were observed to converge very slowly to the true values (in simulated experiments) as the number of constraints was increased. To formulate these constraints, prior studies used only the free-interface modes of the fixture or the measured modes of the assembly. This work extends that to consider other sets of constraints, showing improved results. Furthermore, in some prior studies it has been observed that there were errors of more than 10% in the natural frequencies even when the fixture motion was hundreds of times smaller than the motion of the structure of interest (and so it had presumably been removed). This work explores this phenomenon, seeking to use the strain energy in the fixture, to the extent that it can be estimated using a test-analysis model for the fixture, as a metric to predict frequency error. The proposed methods are explored by applying them to simulated measurements from a beam and from the NASA Space Launch System coupled to the Mobile Launcher

Online alignment of human motion using forward plotting‐dynamic time warping

A number of approaches to online time warping have been proposed based on plotting an alignment path backwards from a selected end-point. When continually updating a time warp to align a time series with a live data source, such as a stream of motion capture data, the use of backwards plotting makes it hard to maintain a monotonic constraint. To solve this problem, a number of time warping approaches based on forward plotting, referred to as FP-DTW, are proposed and evaluated by applying them to human motions. We demonstrate that forward plotting for temporal alignment is a viable solution when backwards plotting is otherwise not possible

Correlation as a measure for alignment and similarity of human motions

The ability to measure similarity and alignment of motions is a key tool in motion retrieval and motion editing. Similarity metrics based on distance functions are often utilized when measuring similarity of human motions, however, metrics based on correlation can also potentially useful for measuring similarity and alignment. This paper evaluates the use of correlation as a method of measuring the alignment and similarity of human motion and compares them against more established distance-based metrics. Three correlation methods and five methods of parameterising rotation are evaluated. The results show that parameterization based on displacement vectors and Kendall Tau rank correlation are optimal for measuring the alignment between two motions. If measuring similarity of motions, however, an approach based on distance metrics for angular or positional distance should be used

A Satellite-Based Multi-Pollutant Index of Global Air Quality

Air pollution is a major health hazard that is responsible formillions of annual excess deaths worldwide. Simpleindicators are useful for comparative studies and to asses strends over time. The development of global indicators hasbeen impeded by the lack of ground-based observations in vast regions of the world. Recognition is growing of the need for amultipollutant approach to air quality to better represent human exposure. Here we introduce the prospect of amultipollutant air quality indicator based on observations from satellite remote sensing

Efficacy of CMX001 as a Prophylactic and Presymptomatic Antiviral Agent in New Zealand White Rabbits Infected with Rabbitpox Virus, a Model for Orthopoxvirus Infections of Humans

CMX001, a lipophilic nucleotide analog formed by covalently linking 3-(hexdecyloxy)propan-1-ol to cidofovir (CDV), is being developed as a treatment for smallpox. CMX001 has dramatically increased potency versus CDV against all dsDNA viruses and, in contrast to CDV, is orally available and has shown no evidence of nephrotoxicity in healthy volunteers or severely ill transplant patients to date. Although smallpox has been eliminated from the environment, treatments are urgently being sought due to the risk of smallpox being used as a bioterrorism agent and for monkeypox virus, a zoonotic disease of Africa, and adverse reactions to smallpox virus vaccinations. In the absence of human cases of smallpox, new treatments must be tested for efficacy in animal models. Here we first review and discuss the rabbitpox virus (RPV) infection of New Zealand White rabbits as a model for smallpox to test the efficacy of CMX001 as a prophylactic and early disease antiviral. Our results should also be applicable to monkeypox virus infections and for treatment of adverse reactions to smallpox vaccination

North American Pollution Outflow and the Trapping of Convectively Lifted Pollution by Upper-Level Anticyclone

We examine the major outflow pathways for North American pollution to the Atlantic in summer by conducting a 4-year simulation with the GEOS-CHEM global chemical transport model, including a coupled ozone-aerosol simulation with 1° × 1° horizontal resolution for summer 2000. The outflow is driven principally by cyclones tracking eastward across North America at 45–55°N, every 5 days on average. Anthropogenic and fire effluents from western North America are mostly transported north and east, eventually merging with the eastern U.S. pollution outflow to the Atlantic. A semipermanent upper-level anticyclone traps the convective outflow and allows it to age in the upper troposphere over the United States for several days. Rapid ozone production takes place in this outflow, driven in part by anthropogenic and lightning NO x and in part by HO x radicals produced from convectively lifted CH2O that originates from biogenic isoprene. This mechanism could explain ozonesonde observations of elevated ozone in the upper troposphere over the southeastern United States. Asian and European pollution influences in the North American outflow to the Atlantic are found to be dispersed into the background and do not generate distinct plumes. Satellite observations of CO columns from MOPITT and of aerosol optical depths (AODs) from MODIS provide useful mapping of outflow events, despite their restriction to clear-sky scenes.Earth and Planetary Science