Interactive lounge : an interdisciplinary approach to the design of a gestural interaction device

Among the many new opportunities that digital technologies are enabling are an increased capacity for viewers to interact not only with the program content, but with an increasingly wide array of other digital applications. Within this context this project has developed a new interaction device (incorporating gestural platform technology) and user interfaces to facilitate interactive access to digital media in a lounge room setting. This paper provides an overview of an interdisciplinary design process applied by Australasian CRC for Interaction Design (ACID) researchers—in order to develop the device and present in detail its unique features.

Rare chromosome disorders and their developmental consequences

Professionals working in disability services often encounter clients who have chromosome disorders such as Williams, Angelman or Down syndromes. As chromosome testing becomes increasingly sophisticated, however, more people are being diagnosed with very rare chromosome disorders that are identified not by a syndrome name, but rather by a description of the number, size and shape of their chromosomes (called the karyotype) or by a report of chromosome losses and gains detected through an advanced process known as microarray-based comparative genomic hybridisation (array CGH). For practitioners who work with individuals with rare chromosome disorders and their families, a basic level of knowledge about the evolving field of genetics, as well as specific knowledge about chromosome abnormalities, is essential since they must be able to demonstrate their knowledge and skills to clients (Simic & Turk, 2004). In addition, knowledge about the developmental consequences of various rare chromosome disorders is important for guiding prognoses, expectations, decisions and interventions. The current article provides information that aims to help practitioners work more effectively with this population. It begins by presenting essential information about chromosomes and their numerical and structural abnormalities and then considers the developmental consequences of rare chromosome disorders through a critical review of relevant literature.

Fuzzy associative memory for humanoid robot joint control

Traditional approaches to joint control required accurate modelling of the system dynamic of the plant in question. Fuzzy Associative Memory (FAM) control schemes allow adequate control without a model of the system to be controlled. This paper presents a FAM based joint controller implemented on a humanoid robot. An empirically tuned PI velocity control loop is augmented with this feed forward FAM, with considerable reduction in joint position error achieved online and with minimal additional computational overhead.

Semi-analytic method of contact modelling

An algorithm to improve the accuracy and stability of rigid-body contact force calculation is presented. The algorithm uses a combination of analytic solutions and numerical methods to solve a spring-damper differential equation typical of a contact model. The solution method employs the recently proposed patch method, which especially suits the spring-damper differential equations. The resulting semi-analytic solution reduces the stiffness of the differential equations, while performing faster than conventional alternatives.

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.

Talk2Me : the art of augmenting conversations

This paper describes an interactive installation work set in a large dome space. The installation is an audio and physical re-rendition of an interactive writing work. In the original work, the user interacted via keyboard and screen while online. This rendition of the work retains the online interaction, but also places the interaction within a physical space, where the main 'conversation' takes place by the participant-audience speaking through microphones and listening through headphones. The work now also includes voice and SMS input, using speech-to-text and text-to-speech conversion technologies, and audio and displayed text for output. These additions allow the participant-audience to co-author the work while they participate in audible conversation with keyword-triggering characters (bots). Communication in the space can be person-to-computer via microphone, keyboard, and phone; person-to-person via machine and within the physical space; computer-to- computer; and computer-to-person via audio and projected text.

Evaluating viewpoint entropy for ribbon representation of protein structure

While many measures of viewpoint goodness have been proposed in computer graphics, none have been evaluated for ribbon representations of protein secondary structure. To fill this gap, we conducted a user study on Amazon’s Mechanical Turk platform, collecting human viewpoint preferences from 65 participants for 4 representative su- perfamilies of protein domains. In particular, we evaluated viewpoint entropy, which was previously shown to be a good predictor for human viewpoint preference of other, mostly non-abstract objects. In a second study, we asked 7 molecular biology experts to find the best viewpoint of the same protein domains and compared their choices with viewpoint entropy. Our results show that viewpoint entropy overall is a significant predictor of human viewpoint preference for ribbon representations of protein secondary structure. However, the accuracy is highly dependent on the complexity of the structure: while most participants agree on good viewpoints for small, non-globular structures with few secondary structure elements, viewpoint preference varies considerably for complex structures. Finally, experts tend to choose viewpoints of both low and high viewpoint entropy to emphasize different aspects of the respective structure.