Book review "Moving Innovation: A History of Computer Animation by Tom Sito , The MIT Press: Cambridge, MA, 2013"

As a Lecturer of Animation History and 3D Computer Animator, I received a copy of Moving Innovation: A History of Computer Animation by Tom Sito with an element of anticipation in the hope that this text would clarify the complex evolution of Computer Graphics (CG). Tom Sito did not disappoint, as this text weaves together the multiple development streams and convergent technologies and techniques throughout history that would ultimately result in modern CG. Universities now have students who have never known a world without computer animation and many students are younger than the first 3D CG animated feature film, Toy Story (1996); this text is ideal for teaching computer animation history and, as I would argue, it also provides a model for engaging young students in the study of animation history in general. This is because Sito places the development of computer animation within the context of its pre-digital ancestry and throughout the text he continues to link the discussion to the broader history of animation, its pioneers, technologies and techniques...

An efficient and robust system for multi-person event detection in real world indoor surveillance scenes

Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).

The N170 observed ‘in the wild’: robust event-related potentials to faces in cluttered dynamic visual scenes

As a social species in a constantly changing environment, humans rely heavily on the informational richness and communicative capacity of the face. Thus, understanding how the brain processes information about faces in real-time is of paramount importance. The N170 is a high temporal resolution electrophysiological index of the brain's early response to visual stimuli that is reliably elicited in carefully controlled laboratory-based studies. Although the N170 has often been reported to be of greatest amplitude to faces, there has been debate regarding whether this effect might be an artifact of certain aspects of the controlled experimental stimulation schedules and materials. To investigate whether the N170 can be identified in more realistic conditions with highly variable and cluttered visual images and accompanying auditory stimuli we recorded EEG 'in the wild', while participants watched pop videos. Scene-cuts to faces generated a clear N170 response, and this was larger than the N170 to transitions where the videos cut to non-face stimuli. Within participants, wild-type face N170 amplitudes were moderately correlated to those observed in a typical laboratory experiment. Thus, we demonstrate that the face N170 is a robust and ecologically valid phenomenon and not an artifact arising as an unintended consequence of some property of the more typical laboratory paradigm.

An MRF based abnormal event detection approach using motion and appearance features

Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.

Ranking based clustering for social event detection

The problem of clustering a large document collection is not only challenged by the number of documents and the number of dimensions, but it is also affected by the number and sizes of the clusters. Traditional clustering methods fail to scale when they need to generate a large number of clusters. Furthermore, when the clusters size in the solution is heterogeneous, i.e. some of the clusters are large in size, the similarity measures tend to degrade. A ranking based clustering method is proposed to deal with these issues in the context of the Social Event Detection task. Ranking scores are used to select a small number of most relevant clusters in order to compare and place a document. Additionally,instead of conventional cluster centroids, cluster patches are proposed to represent clusters, that are hubs-like set of documents. Text, temporal, spatial and visual content information collected from the social event images is utilized in calculating similarity. Results show that these strategies allow us to have a balance between performance and accuracy of the clustering solution gained by the clustering method.

Adapting “8-bit” motion style to 3D computer animation for Wreck-it Ralph

Tangled (2011) demonstrated that Walt Disney Animation has successfully extended the traditional Disney animation aesthetic to the 3D medium. The very next film produced by the studio however, Wreck-it Ralph (2012), required the animators (trained in the traditional Disney style) to develop a limited style of animation inspired by the 8-bit motion of 1980s video games. This paper examines the 8-bit style motion in Wreck-it Ralph to understand if and how the principles of animation were adapted for the film.

SAIVT-ADMRG @ MediaEval 2014 social event detection

This paper outlines the approach taken by the Speech, Audio, Image and Video Technologies laboratory, and the Applied Data Mining Research Group (SAIVT-ADMRG) in the 2014 MediaEval Social Event Detection (SED) task. We participated in the event based clustering subtask (subtask 1), and focused on investigating the incorporation of image features as another source of data to aid clustering. In particular, we developed a descriptor based around the use of super-pixel segmentation, that allows a low dimensional feature that incorporates both colour and texture information to be extracted and used within the popular bag-of-visual-words (BoVW) approach.

Development of a log-quadratic model to describe microbial inactivation, illustrated by thermal inactivation of Clostridium botulinum

In the commercial food industry, demonstration of microbiological safety and thermal process equivalence often involves a mathematical framework that assumes log-linear inactivation kinetics and invokes concepts of decimal reduction time (DT), z values, and accumulated lethality. However, many microbes, particularly spores, exhibit inactivation kinetics that are not log linear. This has led to alternative modeling approaches, such as the biphasic and Weibull models, that relax strong log-linear assumptions. Using a statistical framework, we developed a novel log-quadratic model, which approximates the biphasic and Weibull models and provides additional physiological interpretability. As a statistical linear model, the log-quadratic model is relatively simple to fit and straightforwardly provides confidence intervals for its fitted values. It allows a DT-like value to be derived, even from data that exhibit obvious "tailing." We also showed how existing models of non-log-linear microbial inactivation, such as the Weibull model, can fit into a statistical linear model framework that dramatically simplifies their solution. We applied the log-quadratic model to thermal inactivation data for the spore-forming bacterium Clostridium botulinum and evaluated its merits compared with those of popular previously described approaches. The log-quadratic model was used as the basis of a secondary model that can capture the dependence of microbial inactivation kinetics on temperature. This model, in turn, was linked to models of spore inactivation of Sapru et al. and Rodriguez et al. that posit different physiological states for spores within a population. We believe that the log-quadratic model provides a useful framework in which to test vitalistic and mechanistic hypotheses of inactivation by thermal and other processes. Copyright © 2009, American Society for Microbiology. All Rights Reserved.

Strolls project and website

The Strolls project was originally devised for a colleague in Finland and a cross cultural event event called AU goes to FI – the core concept is both re-experience of and presentation of the ‘everyday’ experience of life rather than the usual cultural icons. The project grew and was presented as a mash-up site with google maps (truna aka j.turner & David Browning). The site is now cob-webbed but some of the participant made strolls are archived here. The emphasis on the walk and taking of image stills (as opposed to the straightforward video) is based on a notion of partaking of the environment with technology. The process involves a strange and distinct embodiment as the maker must stop and choose each subsequent shot in order to build up the final animated sequence. The viewer becomes subtly involved in the maker’s decisions.

Functional neuroanatomy of auditory mismatch processing : an event-related fMRI study of duration-deviant oddballs

This study was designed to identify the neural networks underlying automatic auditory deviance detection in 10 healthy subjects using functional magnetic resonance imaging. We measured blood oxygenation level-dependent contrasts derived from the comparison of blocks of stimuli presented as a series of standard tones (50 ms duration) alone versus blocks that contained rare duration-deviant tones (100 ms) that were interspersed among a series of frequent standard tones while subjects were watching a silent movie. Possible effects of scanner noise were assessed by a “no tone” condition. In line with previous positron emission tomography and EEG source modeling studies, we found temporal lobe and prefrontal cortical activation that was associated with auditory duration mismatch processing. Data were also analyzed employing an event-related hemodynamic response model, which confirmed activation in response to duration-deviant tones bilaterally in the superior temporal gyrus and prefrontally in the right inferior and middle frontal gyri. In line with previous electrophysiological reports, mismatch activation of these brain regions was significantly correlated with age. These findings suggest a close relationship of the event-related hemodynamic response pattern with the corresponding electrophysiological activity underlying the event-related “mismatch negativity” potential, a putative measure of auditory sensory memory.

The second chance project: A multi-level examination of secondary prevention practices for Saudi people following a recent cardiac event

The study examined the health-related behaviours of Saudi people following a recent cardiac event and identified the factors that influence these behaviours using McLeroy et al.'s (1988) Ecological Model of Health Behaviours as a guiding framework. The study was one of the first in Saudi Arabia to examine the health-related behaviours of Saudi people following a recent cardiac event. The study findings emphasise the importance of a program that integrates secondary prevention practices, educational approaches and targeted supportive services in cardiac care in Saudi Arabia.

Stress during the rebuilding phase influenced mental health following two Queensland flood disasters more than the event itself

It has long been known that disasters can have mental health consequences such as increased rates of PTSD, depression and anxiety. While some research has shown that secondary stressors during the aftermath of a disaster can influence psychological outcomes, this aspect of the disaster experience has not been widely studied. This paper reports on two studies that investigated which aspects of the experience of being flooded were most predictive of mental health outcomes. The first study was a qualitative study of adults whose homes had been inundated in the Mackay flood of 2008 (n=16). Thematic analysis of interviews conducted 18-20 months post-flood found that stressors during the flood aftermath such as difficulties and delays during the rebuilding process and a difficult experience with an insurance company were nominated as the most stressful aspect of the flood by the majority of participants. The second study surveyed Mackay flood survivors three and a half years post-flood, and Brisbane 2011 flood survivors 7-9 months post-flood (n=158). Findings indicated aftermath stress contributed to mental health outcomes over and above the contribution of perceived trauma, objective flood severity, prior mental health, self-efficacy and demographic factors. The implications of these results for the provision of community recovery services following natural disasters are discussed, including the need to provide effective targeting of support services throughout the lengthy rebuilding phase; a possible role for co-ordinating tradespeople; and training for insurance company staff aimed at minimising the incidence of insurance company staff inadvertently adding to disaster victims’ stress.