Lumia : art/light/motion

Lumia: art/light/motion is an exciting new media exhibition presented by State Library of Queensland in partnership with Queensland-based Kuuki collective artists Priscilla Bracks and Gavin Sade. The exhibition explored contemporary life and encourages thought about the future through an extraordinary collection of hand-crafted and interactive electronic creatures and installations. The beautifully crafted new media artworks in Lumia: art/light/motion combine the bespoke with art and technology to create strange but intriguing objects. Lumia invited audiences to play, learn and then ponder the way we live and the environmental and social implications of our choices.

A distributed protocol for object tracking in wireless multimedia sensor networks

We consider the problem of object tracking in a wireless multimedia sensor network (we mainly focus on the camera component in this work). The vast majority of current object tracking techniques, either centralised or distributed, assume unlimited energy, meaning these techniques don't translate well when applied within the constraints of low-power distributed systems. In this paper we develop and analyse a highly-scalable, distributed strategy to object tracking in wireless camera networks with limited resources. In the proposed system, cameras transmit descriptions of objects to a subset of neighbours, determined using a predictive forwarding strategy. The received descriptions are then matched at the next camera on the objects path using a probability maximisation process with locally generated descriptions. We show, via simulation, that our predictive forwarding and probabilistic matching strategy can significantly reduce the number of object-misses, ID-switches and ID-losses; it can also reduce the number of required transmissions over a simple broadcast scenario by up to 67%. We show that our system performs well under realistic assumptions about matching objects appearance using colour.

Intelligent physical modelling systems - Why?

“What did you think you were doing?” Was the question posed by the conference organizers to me as the inventor and constructor of the first working Tangible Interfaces over 40 years ago. I think the question was intended to encourage me to talk about the underlying ideas and intentionality rather than describe an endless sequence of electronic bricks and that is what I shall do in this presentation. In the sixties the prevalent idea for a graphics interface was an analogue with sketching which was to somehow be understood by the computer as three dimensional form. I rebelled against this notion for reasons which I will explain in the presentation and instead came up with tangible physical three dimensional intelligent objects. I called these first prototypes “Intelligent Physical Modelling Systems” which is a really dumb name for an obvious concept. I am eternally grateful to Hiroshi Ishii for coining the term “Tangible User Interfaces” - the same idea but with a much smarter name. Another motivator was user involvement in the design process, and that led to the Generator (1979) project with Cedric Price for the world’s first intelligent building capable of organizing itself in response to the appetites of the users. The working model of that project is in MoMA. And the same motivation led to a self builders design kit (1980) for Walter Segal which facilitated self-builders to design their own houses. And indeed as the organizer’s question implied, the motivation and intentionality of these projects developed over the years in step with advancing technology. The speaker will attempt to articulate these changes with medical, psychological and educational examples. Much of this later work indeed stemming from the Media Lab where we are talking. Related topics such as “tangible thinking” and “intelligent teacups” will be introduced and the presentation will end with some speculations for the future. The presentation will be given against a background of images of early prototypes many of which have never been previously published.

Slum free India program. Report on the findings and recommendations of QUT BEE workshop to investigate strategies to deliver better outcomes

As a result of a broad invitation extended by Professor Martin Betts, Executive Dean of the Faculty of Built Environment and Engineering, to the community of interest at QUT, a cross-disciplinary collaborative workshop was conducted to contribute ideas about responding to the Government of India’s urgent requirement to implement a program to re-house slum dwellers. This is a complex problem facing the Indian Ministry of Housing. Not only does the government aspire to eradicate existing slum conditions and to achieve tangible results within five years, but it must also ensure that slums do not form in the future. The workshop focused on technological innovation in construction to deliver transformation from the current unsanitary and overcrowded informal urban settlements to places that provide the economically weaker sections of Indian society with healthy, environmentally sustainable, economically viable mass housing that supports successful urban living. The workshop was conducted in two part process as follows: Initially, QUT academics from diverse fields shared current research and provided technical background to contextualise the challenge at a pre-workshop briefing session. This was followed by a one-day workshop during which participants worked intensively in multi-disciplinary groups through a series of exercises to develop innovative approaches to the complex problem of slum redevelopment. Dynamic, compressed work sessions, interspersed with cross-functional review and feedback by the whole group took place throughout the day. Reviews emphasised testing the concepts for their level of complexity, and likelihood of success. The two-stage workshop process achieved several objectives:  Inspired a sense of shared purpose amongst a diverse group of academics  Built participants’ knowledge of each other’s capacity  Engaged multi disciplinary team in an innovative design research process  Built participants’ confidence in the collaborative process  Demonstrated that collaborative problem solving can create solutions that represent transformative change.  Developed a framework of how workable solutions might be developed for the program through follow up workshops and charrettes of a similar nature involving stakeholders drawn from the context of the slum housing program management.

Applying ISOMAP to the learning of hyperspectral image

In this paper, we present the application of a non-linear dimensionality reduction technique for the learning and probabilistic classification of hyperspectral image. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. It gives much greater information content per pixel on the image than a normal colour image. This should greatly help with the autonomous identification of natural and manmade objects in unfamiliar terrains for robotic vehicles. However, the large information content of such data makes interpretation of hyperspectral images time-consuming and userintensive. We propose the use of Isomap, a non-linear manifold learning technique combined with Expectation Maximisation in graphical probabilistic models for learning and classification. Isomap is used to find the underlying manifold of the training data. This low dimensional representation of the hyperspectral data facilitates the learning of a Gaussian Mixture Model representation, whose joint probability distributions can be calculated offline. The learnt model is then applied to the hyperspectral image at runtime and data classification can be performed.

Design of a model-generated repository as a service for USDL

SAP and its research partners have been developing a lan- guage for describing details of Services from various view- points called the Unified Service Description Language (USDL). At the time of writing, version 3.0 describes technical implementation aspects of services, as well as stakeholders, pricing, lifecycle, and availability. Work is also underway to address other business and legal aspects of services. This language is designed to be used in service portfolio management, with a repository of service descriptions being available to various stakeholders in an organisation to allow for service prioritisation, development, deployment and lifecycle management. The structure of the USDL metadata is specified using an object-oriented metamodel that conforms to UML, MOF and EMF Ecore. As such it is amenable to code gener-ation for implementations of repositories that store service description instances. Although Web services toolkits can be used to make these programming language objects available as a set of Web services, the practicalities of writing dis- tributed clients against over one hundred class definitions, containing several hundred attributes, will make for very large WSDL interfaces and highly inefficient “chatty” implementations. This paper gives the high-level design for a completely model-generated repository for any version of USDL (or any other data-only metamodel), which uses the Eclipse Modelling Framework’s Java code generation, along with several open source plugins to create a robust, transactional repository running in a Java application with a relational datastore. However, the repository exposes a generated WSDL interface at a coarse granularity, suitable for distributed client code and user-interface creation. It uses heuristics to drive code generation to bridge between the Web service and EMF granularities.

Graphcut-based interactive segmentation using colour and depth cues

Segmentation of novel or dynamic objects in a scene, often referred to as background sub- traction or foreground segmentation, is critical for robust high level computer vision applica- tions such as object tracking, object classifca- tion and recognition. However, automatic real- time segmentation for robotics still poses chal- lenges including global illumination changes, shadows, inter-re ections, colour similarity of foreground to background, and cluttered back- grounds. This paper introduces depth cues provided by structure from motion (SFM) for interactive segmentation to alleviate some of these challenges. In this paper, two prevailing interactive segmentation algorithms are com- pared; Lazysnapping [Li et al., 2004] and Grab- cut [Rother et al., 2004], both based on graph- cut optimisation [Boykov and Jolly, 2001]. The algorithms are extended to include depth cues rather than colour only as in the original pa- pers. Results show interactive segmentation based on colour and depth cues enhances the performance of segmentation with a lower er- ror with respect to ground truth.

Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modelling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modelling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modelling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.

Semi-supervised intelligent surveillance system for secure environments

This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted.

Distributed object tracking with robot and disjoint camera networks

We describe a novel two stage approach to object localization and tracking using a network of wireless cameras and a mobile robot. In the first stage, a robot travels through the camera network while updating its position in a global coordinate frame which it broadcasts to the cameras. The cameras use this information, along with image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to track the objects. We present results with a nine node indoor camera network to demonstrate that this approach is feasible and offers acceptable level of accuracy in terms of object locations.

A biologically inspired object spectral-texture descriptor and its application to vegetation classification in power-line corridors

The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

A crash avoidance framework for heavy equipment control systems using 3D imaging sensors

This paper presents a preliminary crash avoidance framework for heavy equipment control systems. Safe equipment operation is a major concern on construction sites since fatal on-site injuries are an industry-wide problem. The proposed framework has potential for effecting active safety for equipment operation. The framework contains algorithms for spatial modeling, object tracking, and path planning. Beyond generating spatial models in fractions of seconds, these algorithms can successfully track objects in an environment and produce a collision-free 3D motion trajectory for equipment.

A methodology for object identification and tracking in construction based on spatial modeling and image matching techniques

Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

Textures of optical flow for real-time anomaly detection in crowds

Automated visual surveillance of crowds is a rapidly growing area of research. In this paper we focus on motion representation for the purpose of abnormality detection in crowded scenes. We propose a novel visual representation called textures of optical flow. The proposed representation measures the uniformity of a flow field in order to detect anomalous objects such as bicycles, vehicles and skateboarders; and can be combined with spatial information to detect other forms of abnormality. We demonstrate that the proposed approach outperforms state-of-the-art anomaly detection algorithms on a large, publicly-available dataset.