"Re-imagining animation : the changing face of the moving image by Paul Wells and Johnny Hardstaff" (Book Review)

Advances in digital technology have caused a radical shift in moving image culture. This has occurred in both modes of production and sites of exhibition, resulting in a blurring of boundaries that previously defined a range of creative disciplines. Re-Imagining Animation: The Changing Face of the Moving Image, by Paul Wells and Johnny Hardstaff, argues that as a result of these blurred disciplinary boundaries, the term “animation” has become a “catch all” for describing any form of manipulated moving image practice. Understanding animation predicates the need to (re)define the medium within contemporary moving image culture. Via a series of case studies, the book engages with a range of moving image works, interrogating “how the many and varied approaches to making film, graphics, visual artefacts, multimedia and other intimations of motion pictures can now be delineated and understood” (p. 7). The structure and clarity of content make this book ideally suited to any serious study of contemporary animation which accepts animation as a truly interdisciplinary medium.

Person-independent facial expression detection using constrained local models

In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP datasets.

Estoppel in the face of consumer protection in land transactions- judicial reasoning or judicial intuition

Nationally, there is much legislation regulating land sale transactions, particularly in relation to seller disclosure of information. The statutes require strict compliance by a seller failing which, in general, a buyer can terminate the contract. In a number of instances, when buyers have sought to exercise these rights, sellers have alleged that buyers have either expressly or by conduct waived their rights to rely upon these statutes. This article examines the nature of these rights in this context, whether they are capable of waiver and, if so, what words or conduct might be sufficient to amount to waiver. The analysis finds that the law is in a very unsatisfactory state, that the operation of those rules that can be identified as having relevance are unevenly applied and concludes that sellers have, in the main, been unsuccessful in defeating buyers' statutory rights as a result of an alleged waiver by those buyers.

The changing face of practice for developing perception : action skill in cricket

The use of bowling machines is common practice in cricket. In an ideal world all batters would face real bowlers in practice sessions, but this is not always possible, for many reasons. The clear advantage of using bowling machines is that they alleviate the workload required from bowlers (Dennis, Finch & Farhart, 2005) and provide relatively consistent and accurate ball delivery which may not be otherwise available to many young batters. Anecdotal evidence suggests that many, if not most of the world’s greatest players use these methods within their training schedules. For example, Australian internationals, Michael Hussey and Matthew Hayden extensively used bowling machines (Hussey & Sygall, 2007). Bowling machines enable batsmen to practice for long periods, developing their endurance and concentration. However, despite these obvious benefits, in recent times the use of bowling machines has been questioned by sport scientists, coaches, ex- players and commentators. For example, Hussey’s batting coach comments “…we never went near a bowling machine in [Michael’s] first couple of years, I think there’s something to that …” (Hussey & Sygall, 2007, p. 119). This chapter will discuss the efficacy of using bowling machines with reference to research findings, before reporting new evidence that provides support for an alternative, innovative and possibly more representative practice design. Finally, the chapter will provide advice for coaches on the implications of this research, including a case study approach to demonstrate the practical use of such a design.

Face recognition using fractal codes

In this paper we propose a new method for face recognition using fractal codes. Fractal codes represent local contractive, affine transformations which when iteratively applied to range-domain pairs in an arbitrary initial image result in a fixed point close to a given image. The transformation parameters such as brightness offset, contrast factor, orientation and the address of the corresponding domain for each range are used directly as features in our method. Features of an unknown face image are compared with those pre-computed for images in a database. There is no need to iterate, use fractal neighbor distances or fractal dimensions for comparison in the proposed method. This method is robust to scale change, frame size change and rotations as well as to some noise, facial expressions and blur distortion in the image

Face authentication test on the BANCA database

This work details the results of a face authentication test (FAT2004) (http://www.ee.surrey.ac.uk/banca/icpr2004) held in conjunction with the 17th International Conference on Pattern Recognition. The contest was held on the publicly available BANCA database (http://www.ee.surrey.ac.uk/banca) according to a defined protocol (E. Bailly-Bailliere et al., June 2003). The competition also had a sequestered part in which institutions had to submit their algorithms for independent testing. 13 different verification algorithms from 10 institutions submitted results. Also, a standard set of face recognition software packages from the Internet (http://www.cs.colostate.edu/evalfacerec) were used to provide a baseline performance measure.

Super-resolved faces for improved face recognition from surveillance video advances in biometrics

Characteristics of surveillance video generally include low resolution and poor quality due to environmental, storage and processing limitations. It is extremely difficult for computers and human operators to identify individuals from these videos. To overcome this problem, super-resolution can be used in conjunction with an automated face recognition system to enhance the spatial resolution of video frames containing the subject and narrow down the number of manual verifications performed by the human operator by presenting a list of most likely candidates from the database. As the super-resolution reconstruction process is ill-posed, visual artifacts are often generated as a result. These artifacts can be visually distracting to humans and/or affect machine recognition algorithms. While it is intuitive that higher resolution should lead to improved recognition accuracy, the effects of super-resolution and such artifacts on face recognition performance have not been systematically studied. This paper aims to address this gap while illustrating that super-resolution allows more accurate identification of individuals from low-resolution surveillance footage. The proposed optical flow-based super-resolution method is benchmarked against Baker et al.’s hallucination and Schultz et al.’s super-resolution techniques on images from the Terrascope and XM2VTS databases. Ground truth and interpolated images were also tested to provide a baseline for comparison. Results show that a suitable super-resolution system can improve the discriminability of surveillance video and enhance face recognition accuracy. The experiments also show that Schultz et al.’s method fails when dealing surveillance footage due to its assumption of rigid objects in the scene. The hallucination and optical flow-based methods performed comparably, with the optical flow-based method producing less visually distracting artifacts that interfered with human recognition.

Make-buy decisions in the face of technological change: does industry clockspeed matter?

Some evidence in the area of make-buy decisions for new technologies suggests that it is a good idea for a company to pursue a fairly rigorous ''make'' policy in the early days of a potentially disruptive innovation. Other studies prescribe exactly the opposite, promoting instead a ''buy'' strategy. This paper seeks to bridge the gap between these perspectives by suggesting that both strategies are valid, but that they are most successfully applied in different market environments. The ''make'' prescription may be more suited to either extremely fast or extremely slow rates of technological change, while a ''buy'' strategy might be more appropriate in market sectors where technologies evolve at a medium pace. This paper highlights the importance of industry clockspeed and supplier relationships in make-buy decisions for new technologies, and puts forward two new hypotheses that require empirical testing.

Face recognition across pose on video using eigen light-fields

We propose an approach to employ eigen light-fields for face recognition across pose on video. Faces of a subject are collected from video frames and combined based on the pose to obtain a set of probe light-fields. These probe data are then projected to the principal subspace of the eigen light-fields within which the classification takes place. We modify the original light-field projection and found that it is more robust in the proposed system. Evaluation on VidTIMIT dataset has demonstrated that the eigen light-fields method is able to take advantage of multiple observations contained in the video.

Feature-domain super-resolution framework for gabor-based face and iris recognition

The low resolution of images has been one of the major limitations in recognising humans from a distance using their biometric traits, such as face and iris. Superresolution has been employed to improve the resolution and the recognition performance simultaneously, however the majority of techniques employed operate in the pixel domain, such that the biometric feature vectors are extracted from a super-resolved input image. Feature-domain superresolution has been proposed for face and iris, and is shown to further improve recognition performance by capitalising on direct super-resolving the features which are used for recognition. However, current feature-domain superresolution approaches are limited to simple linear features such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which are not the most discriminant features for biometrics. Gabor-based features have been shown to be one of the most discriminant features for biometrics including face and iris. This paper proposes a framework to conduct super-resolution in the non-linear Gabor feature domain to further improve the recognition performance of biometric systems. Experiments have confirmed the validity of the proposed approach, demonstrating superior performance to existing linear approaches for both face and iris biometrics.