Super-realistic rendering using real-time tweening

The realism of contemporary computer graphics (and especially Virtual Reality {VR}) is limited by the great computational cost of rendering objects of appropriate complexity with convincing lighting and surface effects. We introduce a framework that allows rendering of objects in true photographic quality using tweening. The simple but effective design of our system allows us not only to perform the necessary operations in real-time on standard hardware, but also achieve other effects like morphing. Furthermore, it is shown how our system can be gainfully employed in non-VR contexts like extreme low-bandwidth video-conferencing and others.

Real-time observation of fiber network formation in molecular organogel : supersaturation-dependent microstructure and its related rheological property

Low-molecular mass organic gelators self-organizing into three-dimensional fiber networks within organic solvents have attracted much attention in recent years. However, to date, how the microstructure of fiber network is formed in a gelation process and the key factors that govern the topological structure of a gel network remain to be determined. In this work, we address these issues by investigating the in situ formation of the gel networks in the N-lauroyl-l-glutamic acid di-n-butylamide (GP-1)/propylene glycol (PG) system. By using optical microscopy, the time evolution of the gel network microstructure was investigated under various supersaturation conditions. It is found that supersaturation is one of the key factors that govern the topological structure of a gel network. In particular, the creation of the junctions turns out to be supersaturation-dependent. The rheological experiments further revealed the correlation between topological structure and mechanical properties. It suggests that the rheological properties can be effectively modified by tuning the microstructure topology of the gel network. Our results reported here provide new physical insight into the formation kinetics of a molecular gel. Furthermore, this work could be important in constructing and engineering a supramolecular structure for the purpose of applications.

Real-time detection of parked vehicles from multiple image streams

We present a system to detect parked vehicles in a typical commercial parking complex using multiple streams of images captured through IP connected devices. Compared to traditional object detection techniques and machine learning methods, our approach is significantly faster in detection speed in the presence of multiple image streams. It is also capable of comparable accuracy when put to test against existing methods. And this is achieved without the need to train the system that machine learning methods require. Our approach uses a combination of psychological insights obtained from human detection and an algorithm replicating the outcomes of a SVM learner but without the noise that compromises accuracy in the normal learning process. The result is faster detection with comparable accuracy. Our experiments on images captured from a local test site shows very promising results for an implementation that is not only effective and low cost but also opens doors to new parking applications when combined with other technologies.

Real-time, in-situ, extinction spectroscopy studies on silver-nanoseed formation

In this paper, real-time extinction spectroscopy was employed to analyze in situ the fast formation process of silver seeds. The influencing factors for silver-seed formation, including the concentration of the reducer (NaBH 4), the amount of stabilizer (citrate), and the addition procedure of NaBH4, were evaluated. The configuration of the surface plasmon resonance (SPR) spectra of silver nanoparticles, which reflected the morphology of the produced silver seeds, was found to be distinctly affected by the NaBH4 concentration. Homogeneous silver nanoparticles were obtained when the added NaBH4 was lower in concentration than 2.00 mM. In contrast, higher concentrations of reducing agent (>3.00 mM NaBH4) resulted in uneven silver nanoparticles. Mie theory was applied to clarify the correlation of the SPR and the size of the silver seeds. Repeated additions of a small amount of the reducing agent could increase the monodispersity and isotropy of silver seeds. Real-time extinction spectroscopy is a convenient technique that achieves the in-situ and nondestructive measurement of intermediates in the formation process of silver nanoseeds.

Classifying human actions using an incomplete real-time pose skeleton

Currently, most human action recognition systems are trained with feature sets that have no missing data. Unfortunately, the use of human pose estimation models to provide more descriptive features also entails an increased sensitivity to occlusions, meaning that incomplete feature information will be unavoidable for realistic scenarios. To address this, our approach is to shift the responsibility for dealing with occluded pose data away from the pose estimator and onto the action classifier. This allows the use of a simple, real-time pose estimation (stick-figure) that does not estimate the positions of limbs it cannot find quickly. The system tracks people via background subtraction and extracts the (possibly incomplete) pose skeleton from their silhouette. Hidden Markov Models modified to handle missing data are then used to successfully classify several human actions using the incomplete pose features.

A cache-based mobility-aware scheme for real-time continuous media delivery in wireless networks

Providing real-time or continuous media (CM) application services in wireless networks poses a significant challenge, as it requires timely delivery of data in a best-effort network. In this paper, we propose a cache-based scheme for mobility-aware, CM applications. The proposed scheme exploits a previously proposed caching strategy to complement Mobile-IP by placing services closer to migrated mobile nodes. The central idea of this work is based on the migration of sessions in order to facilitate uninterrupted delivery of CM in mobile environments. The performance of the proposed scheme is investigated by simulation studies. In particular, the effect of the proposed scheme on several QoS parameters under varying conditions of mobility and CM data is measured.

Randomised controlled trials and 'unexpected' adverse events associated with newly released drugs : improvements in pharmacovigilance systems are necessary for real-time identification of patient safety risks

Adverse drug events are one of the major causes of morbidity in developed countries, yet the drugs involved in these events have been trialled and approved on the basis of randomised controlled trials (RCTs), regarded as the study design that will produce the best evidence.

Though the focus on adverse drug events has been primarily on processes and outcomes associated with the use of these approved drugs, attention needs to be directed to the way in which the RCT study design is structured. The implementation of controls to achieve internal validity in RCTs may be the very controls that reduce external validity, and contribute to the levels of adverse drug events associated with the release of a new drug to the wider patient population.

An examination of these controls, and the effects they can have on patient safety, underscore the importance of knowing about how the clinical trials of a drug are undertaken, rather than relying only on the recorded outcomes.

As the majority of new drugs are likely to be prescribed to older patients who have one or more comorbidities in addition to that targeted by a new drug, and as the RCTs of those drugs typically under-represent the elderly and exclude patients with multiple comorbidities, timely assessment of drug safety signals is essential.

It is unlikely that regulatory jurisdictions will undertake a reassessment of safety issues for drugs that are already approved. Instead, reliance has been placed on adverse drug event reporting systems. Such systems have a very low reporting rate, and most adverse drug events remain unreported, to the eventual cost to patients and healthcare systems.

This makes it essential for near real-time systems that can pick up safety signals as they occur, so that modifications to the product information (or removal of the drug) can be implemented.

Real-time surface formation using a network of interconnected programmable actuators

This research has explored methods for developing a large interactive dynamic 3D surface using an array of interconnected pneumatically actuated cylinders. People can control the surface using body movement, sound or pre-programmed sequences. The main contribution is a method for accurately positioning cylinders without the need for position feedback.

Real-time motion capture interactive, 3D stereoscopic visualization

Vincs, McCormick and dancers Steph Hutchinson & Megan Beckwith present live motion capture interactive pipelines that visualise the kinematics of a performer’s movement in stereoscopic environments created using the Unity game engine, and discuss their use in Choreotopography (2010) and Choreotopography (2011). This work forms part of Vincs’ ARC Discovery Project Capturing Dance: using motion capture to enhance the creation of innovative Australian dance (DP0987101).

Processing multiple image streams for real-time monitoring of parking lots

We present a system to detect parked vehicles in a typical parking complex using multiple streams of images captured through IP connected devices. Compared to traditional object detection techniques and machine learning methods, our approach is significantly faster in detection speed in the presence of multiple image streams. It is also capable of comparable accuracy when put to test against existing methods. And this is achieved without the need to train the system that machine learning methods require. Our approach uses a combination of psychological insights obtained from human detection and an algorithm replicating the outcomes of a SVM learner but without the noise that compromises accuracy in the normal learning process. Performance enhancements are made on the algorithm so that it operates well in the context of multiple image streams. The result is faster detection with comparable accuracy. Our experiments on images captured from a local test site shows very promising results for an implementation that is not only effective and low cost but also opens doors to new parking applications when combined with other technologies.

Animal-borne sensors successfully capture the real-time thermal properties of ocean basins

Climate change is perhaps the most pressing and urgent environmental issue facing the world today. However our ability to predict and quantify the consequences of this change is severely limited by the paucity of in situ oceanographic measurements. Marine animals equipped with sophisticated oceanographic data loggers to study their behavior offer one solution to this problem because marine animals range widely across the world’s ocean basins and visit remote and often inaccessible locations. However, unlike the information being collected from conventional oceanographic sensing equipment, which has been validated, the data collected from instruments deployed on marine animals over long periods has not. This is the first long-term study to validate in situ oceanographic data collected by animal oceanographers. We compared the ocean temperatures collected by leatherback turtles (Dermochelys coriacea) in the Atlantic Ocean with the ARGO network of ocean floats and could find no systematic errors that could be ascribed to sensor instability. Animal-borne sensors allowed water temperature to be monitored across a range of depths, over entire ocean basins, and, importantly, over long periods and so will play a key role in assessing global climate change through improved monitoring of global temperatures. This finding is especially pertinent given recent international calls for the development and implementation of a comprehensive Earth observation system (see http://iwgeo.ssc.nasa.gov/documents.asp?s=review) that includes the use of novel techniques for monitoring and understanding ocean and climate interactions to address strategic environmental and societal needs.

Emergent effects in massive agent swarms in real-time game environments

 Computational efficiency and hence the scale of agent-based swarm simulations is bound by the nearest neighbour computation for each agent. This article proposes the use of GPU texture memory to implement lookup tables for a spatial partitioning based k-Nearest Neighbours algorithm. These improvements allow simulation of swarms of 220 agents at higher rates than the current best alternative algorithms. This approach is incorporated into an existing framework for simulating steering behaviours allowing for a complete implementation of massive agent swarm simulations, with per agent behaviour preferences, on a Graphics Processing Unit. These simulations have enabled an investigation of the emergent dynamics that occur when massive swarms interact with a choke point in their environment. Various modes of sustained dynamics with temporal and spatial coherence are identified when a critical mass of agents is simulated and some elementary properties are presented. The algorithms presented in this article enable researchers and content designers in games and movies to implement truly massive agent swarms in real time and thus provide a basis for further identification and analysis of the emergent dynamics in these swarms. This will improve not only the scale of swarms used in commercial games and movies but will also improve the reliability of swarm behaviour with respect to content design goals.