Visualising the 48 hour game making challenge

We have always felt that “something very special” was happening in the 48hr and other similar game jams. This “something” is more than the intensity and challenge of the experience, although this certainly has appeal for the participants. We had an intuition that these intense 48 hour game jams exposed something pertinent to the changing shape of the Australian games industry where we see the demise of the late 20th century large studio - the “Night Elf” model and the growth of the small independent model. There are a large number of wider economic and cultural factors around this evolution but our interest is specifically in the change from “industry” to “creative industry” and the growth of games as a cultural media and art practice. If we are correct in our intuition, then illuminating this something also has important ramifications for those courses which teach game and interaction design and development. Rather than undertake a formal ethno-methodological approach, we decided to track as many of the actors in the event as possible. We documented the experience (Keith Novak’s beautiful B&W photography), the individual and their technology (IOGraph mouse tracking), the teams as a group (Time lapse photography) and movement tracking throughout the whole space (Blue tooth phone tracking). The raw data collected has given us opportunity to start a commentary on the “something special” happening in the 48hr.

Improved Subject Identification in Surveillance Video using Super Resolution

The time consuming and labour intensive task of identifying individuals in surveillance video is often challenged by poor resolution and the sheer volume of stored video. Faces or identifying marks such as tattoos are often too coarse for direct matching by machine or human vision. Object tracking and super-resolution can then be combined to facilitate the automated detection and enhancement of areas of interest. The object tracking process enables the automatic detection of people of interest, greatly reducing the amount of data for super-resolution. Smaller regions such as faces can also be tracked. A number of instances of such regions can then be utilized to obtain a super-resolved version for matching. Performance improvement from super-resolution is demonstrated using a face verification task. It is shown that there is a consistent improvement of approximately 7% in verification accuracy, using both Eigenface and Elastic Bunch Graph Matching approaches for automatic face verification, starting from faces with an eye to eye distance of 14 pixels. Visual improvement in image fidelity from super-resolved images over low-resolution and interpolated images is demonstrated on a small database. Current research and future directions in this area are also summarized.

Performing design analysis: game design creativity and the theatre of the impressed

We report and reflect upon the early stages of a research project that endeavours to establish a culture of critical design thinking in a tertiary game design course. We first discuss the current state of the Australian game industry and consider some perceived issues in game design courses and graduate outcomes. The second sec-tion presents our response to these issues: a project in progress which uses techniques originally exploited by Augusto Boal in his work, Theatre of the Oppressed. We appropriate Boal’s method to promote critical design thinking in a games design class. Finally, we reflect on the project and the ontology of design thinking from the perspective of Bruce Archer’s call to reframe design as a ‘third academic art’.

Using game technologies to improve the safety of construction plant operations

Many accidents occur world-wide in the use of construction plant and equipment, and safety training is considered by many to be one of the best approaches to their prevention. However, current safety training methods/tools are unable to provide trainees with the hands-on practice needed. Game technology-based safety training platforms have the potential to overcome this problem in a virtual environment. One such platform is described in this paper - its characteristics are analysed and its possible contribution to safety training identified. This is developed and tested by means of a case study involving three major pieces of construction plant, which successfully demonstrates that the platform can improve the process and performance of the safety training involved in their operation. This research not only presents a new and useful solution to the safety training of construction operations, but illustrates the potential use of advanced technologies in solving construction industry problems in general.

Impact of region-of-interest video coding on perceived quality in mobile video

Effective streaming of video can be achieved by providing more bits to the most important region in the frame at the cost of reduced bits in the less important regions. This strategy can be beneficial for delivering high quality videos in mobile devices, especially when the availability of bandwidth is usually low and limited. While the state-of-the-art video codecs such as H.264 may have been optimised for perceived quality, it is hypothesised that users will give more attention to interesting region/object when watching videos. Therefore, giving a higher quality to region of interest (ROI)while reducing quality of other areas may result in improving the overall perceived quality without necessarily increasing the bitrate. In this paper, the impact of ROI-based encoded video on perceived quality is investigated by conducting a user study for varous target bitrates. The results from the user study demonstrate that ROI-based video coding has superior perceived quality compared to normal encoded video at the same bitrate in the lower bitrate range.

Measuring reef complexity and rugosity from monocular video bathymetric reconstruction

Topographic structural complexity of a reef is highly correlated to coral growth rates, coral cover and overall levels of biodiversity, and is therefore integral in determining ecological processes. Modeling these processes commonly includes measures of rugosity obtained from a wide range of different survey techniques that often fail to capture rugosity at different spatial scales. Here we show that accurate estimates of rugosity can be obtained from video footage captured using underwater video cameras (i.e., monocular video). To demonstrate the accuracy of our method, we compared the results to in situ measurements of a 2m x 20m area of forereef from Glovers Reef atoll in Belize. Sequential pairs of images were used to compute fine scale bathymetric reconstructions of the reef substrate from which precise measurements of rugosity and reef topographic structural complexity can be derived across multiple spatial scales. To achieve accurate bathymetric reconstructions from uncalibrated monocular video, the position of the camera for each image in the video sequence and the intrinsic parameters (e.g., focal length) must be computed simultaneously. We show that these parameters can be often determined when the data exhibits parallax-type motion, and that rugosity and reef complexity can be accurately computed from existing video sequences taken from any type of underwater camera from any reef habitat or location. This technique provides an infinite array of possibilities for future coral reef research by providing a cost-effective and automated method of determining structural complexity and rugosity in both new and historical video surveys of coral reefs.

Towards spontaneous facial expression recognition in real-world video

Facial expression is an important channel of human social communication. Facial expression recognition (FER) aims to perceive and understand emotional states of humans based on information in the face. Building robust and high performance FER systems that can work in real-world video is still a challenging task, due to the various unpredictable facial variations and complicated exterior environmental conditions, as well as the difficulty of choosing a suitable type of feature descriptor for extracting discriminative facial information. Facial variations caused by factors such as pose, age, gender, race and occlusion, can exert profound influence on the robustness, while a suitable feature descriptor largely determines the performance. Most present attention on FER has been paid to addressing variations in pose and illumination. No approach has been reported on handling face localization errors and relatively few on overcoming facial occlusions, although the significant impact of these two variations on the performance has been proved and highlighted in many previous studies. Many texture and geometric features have been previously proposed for FER. However, few comparison studies have been conducted to explore the performance differences between different features and examine the performance improvement arisen from fusion of texture and geometry, especially on data with spontaneous emotions. The majority of existing approaches are evaluated on databases with posed or induced facial expressions collected in laboratory environments, whereas little attention has been paid on recognizing naturalistic facial expressions on real-world data. This thesis investigates techniques for building robust and high performance FER systems based on a number of established feature sets. It comprises of contributions towards three main objectives: (1) Robustness to face localization errors and facial occlusions. An approach is proposed to handle face localization errors and facial occlusions using Gabor based templates. Template extraction algorithms are designed to collect a pool of local template features and template matching is then performed to covert these templates into distances, which are robust to localization errors and occlusions. (2) Improvement of performance through feature comparison, selection and fusion. A comparative framework is presented to compare the performance between different features and different feature selection algorithms, and examine the performance improvement arising from fusion of texture and geometry. The framework is evaluated for both discrete and dimensional expression recognition on spontaneous data. (3) Evaluation of performance in the context of real-world applications. A system is selected and applied into discriminating posed versus spontaneous expressions and recognizing naturalistic facial expressions. A database is collected from real-world recordings and is used to explore feature differences between standard database images and real-world images, as well as between real-world images and real-world video frames. The performance evaluations are based on the JAFFE, CK, Feedtum, NVIE, Semaine and self-collected QUT databases. The results demonstrate high robustness of the proposed approach to the simulated localization errors and occlusions. Texture and geometry have different contributions to the performance of discrete and dimensional expression recognition, as well as posed versus spontaneous emotion discrimination. These investigations provide useful insights into enhancing robustness and achieving high performance of FER systems, and putting them into real-world applications.

Can you describe him for me? A technique for semantic person search in video

From a law enforcement standpoint, the ability to search for a person matching a semantic description (i.e. 1.8m tall, red shirt, jeans) is highly desirable. While a significant research effort has focused on person re-detection (the task of identifying a previously observed individual in surveillance video), these techniques require descriptors to be built from existing image or video observations. As such, person re-detection techniques are not suited to situations where footage of the person of interest is not readily available, such as a witness reporting a recent crime. In this paper, we present a novel framework that is able to search for a person based on a semantic description. The proposed approach uses size and colour cues, and does not require a person detection routine to locate people in the scene, improving utility in crowded conditions. The proposed approach is demonstrated with a new database that will be made available to the research community, and we show that the proposed technique is able to correctly localise a person in a video based on a simple semantic description.

Ideas as "possessitives" : claims and counter claims in a playground dispute

In the shared space of a school playground, matters of ownership and possession are seriously attended to by children in their everyday encounters with others. The study reported here uses conversation analysis and an ethnomethodological approach to investigate a dispute between two children, aged four to six years, as they decide whose idea for the game will be used. Drawing on Sacks’ (1995a) notion of possession, and Sharrock’s (1974) paper “on owning knowledge”, this paper demonstrates how children draw on the phrase, “that’s my idea”, to claim ownership. Analysis of their video-recorded interaction shows how the children used physical actions, gaze and talk to invoke their own intellectual property as a commodity in the dispute. Whilst invoking ownership, analysis highlights that entitlement over people, objects and the decisions of the shared interactional space did not occur unproblematically. Material objects were used to counter claims to ideas, and it was the uptake of the game and the use of play objects by others that led to whether the idea of game category was upheld. This analysis enables adults a glimpse into the complex social organisation of children’s peer group.

Real-time power line extraction from unmanned aerial system video images

In this paper a real-time vision based power line extraction solution is investigated for active UAV guidance. The line extraction algorithm starts from ridge points detected by steerable filters. A collinear line segments fitting algorithm is followed up by considering global and local information together with multiple collinear measurements. GPU boosted algorithm implementation is also investigated in the experiment. The experimental result shows that the proposed algorithm outperforms two baseline line detection algorithms and is able to fitting long collinear line segments. The low computational cost of the algorithm make suitable for real-time applications.

Mystery at the library : encouraging library exploration using a pervasive mobile game

This paper presents Secret SLQ, a pervasive mobile game that aims to encourage eight to fourteen year olds to engage with the State Library of Queensland. The game sets out to encourage people to visit and explore the library, as well as educate a generation of young people and parents who may visit the library but have no idea of the treasures that it holds. The research explores how smartphone technology can be used to deliver an engaging and educational experience. The game aims to provide a fun and interactive way to guide participants through a multi-leveled library building, to search for unique QR codes to unlock clues, answer quiz questions and progress further up a leaderboard. This paper outlines the design and initial deployment of the game, reporting on results from a usability study and discussing initial observations made by librarians. Findings indicate that the mobile platform is suitable for delivering such experiences but consideration is needed when embedding games in such large environments so as not to confuse players as they play.

Quality based frame selection for video face recognition

Quality based frame selection is a crucial task in video face recognition, to both improve the recognition rate and to reduce the computational cost. In this paper we present a framework that uses a variety of cues (face symmetry, sharpness, contrast, closeness of mouth, brightness and openness of the eye) to select the highest quality facial images available in a video sequence for recognition. Normalized feature scores are fused using a neural network and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face recognition system. Experiments on the Honda/UCSD database shows that the proposed method selects the best quality face images in the video sequence, resulting in improved recognition performance.