Unusual scene detection using distributed behaviour model and sparse representation

The ability to detect unusual events in surviellance footage as they happen is a highly desireable feature for a surveillance system. However, this problem remains challenging in crowded scenes due to occlusions and the clustering of people. In this paper, we propose using the Distributed Behavior Model (DBM), which has been widely used in computer graphics, for video event detection. Our approach does not rely on object tracking, and is robust to camera movements. We use sparse coding for classification, and test our approach on various datasets. Our proposed approach outperforms a state-of-the-art work which uses the social force model and Latent Dirichlet Allocation.

Robust facial feature extraction and matching

Automated feature extraction and correspondence determination is an extremely important problem in the face recognition community as it often forms the foundation of the normalisation and database construction phases of many recognition and verification systems. This paper presents a completely automatic feature extraction system based upon a modified volume descriptor. These features form a stable descriptor for faces and are utilised in a reversible jump Markov chain Monte Carlo correspondence algorithm to automatically determine correspondences which exist between faces. The developed system is invariant to changes in pose and occlusion and results indicate that it is also robust to minor face deformations which may be present with variations in expression.

Modelling passenger flow at airport terminals : individual agent decision model for stochastic passenger behaviour

Airport system is complex. Passenger dynamics within it appear to be complicate as well. Passenger behaviours outside standard processes are regarded more significant in terms of public hazard and service rate issues. In this paper, we devised an individual agent decision model to simulate stochastic passenger behaviour in airport departure terminal. Bayesian networks are implemented into the decision making model to infer the probabilities that passengers choose to use any in-airport facilities. We aim to understand dynamics of the discretionary activities of passengers.

Content sharing on public screens: experiences through iterating social and spatial contexts

This paper describes the design and study of public urban screen applications aiming to facilitate urban dwellers to control content shown on public urban screens. Two types of content sharing are presented: aggregating existing social media content about particular locations for sharing, and sharing online videos with collocated people at a public urban screen. The paper describes an exploratory study, an observational study, as well as an interpretational study in regards to application usage and user experience. Sharing content on public urban screens can pique the curiosity of users towards collocated people and the application itself resulting in raised awareness of collocated people.

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.

A database for person re-identification in multi-camera surveillance networks

Person re-identification involves recognising individuals in different locations across a network of cameras and is a challenging task due to a large number of varying factors such as pose (both subject and camera) and ambient lighting conditions. Existing databases do not adequately capture these variations, making evaluations of proposed techniques difficult. In this paper, we present a new challenging multi-camera surveillance database designed for the task of person re-identification. This database consists of 150 unscripted sequences of subjects travelling in a building environment though up to eight camera views, appearing from various angles and in varying illumination conditions. A flexible XML-based evaluation protocol is provided to allow a highly configurable evaluation setup, enabling a variety of scenarios relating to pose and lighting conditions to be evaluated. A baseline person re-identification system consisting of colour, height and texture models is demonstrated on this database.

Please take out your phones : on the spot solicitation of student feedback in class

The use of mobile devices such as smart phones and tablets in classrooms has been met with mixed sentiments. Some instructors and teachers see them as a distraction and regularly ban their usage. Others who see their potential to enhance learning have started to explore ways to integrate them into their teaching in an attempt to improve student engagement. In this paper we report on a pilot study that forms part of a university-wide project reconceptualising its approach to the student evaluation of learning and teaching. In a progressive decision to embrace mobile technology, the university decided to trial a smart phone app designed for students to check-in to class and leave feedback on the spot. Our preliminary findings from trialling the app indicate that the application establishes a more immediate feedback loop between students and teachers. However, the app’s impact depends on how feedback is shared with students and how the teaching team responds.

Colour coding the fridge to reduce food waste

This paper introduces the first iteration of a study aimed at grouping similar food types together in a refrigerator to increase the awareness of available foods for consumers in a domestic environment. The goals of the project are twofold: i) Raise the awareness of available foods for all members of a household; ii) Reduce the amount of expired food waste in the household. The project implemented a paper-based colour scheme in refrigerators in households, assigning colours to particular food types (e.g. green to fruit and vegetables, red to meat, etc.). The findings show that the colour coding raised participants’ awareness of available food items in the fridge, particularly for those participants who were not directly involved in the shopping and initial storage of each food item. The findings also indicate that such awareness led to a reduction in expiration of food and thus general food waste in the household. These preliminary findings suggest that raising awareness of food availability through categorisation and efficient communication of this information may lead to a reduction in food waste in domestic environments.

Multi-cursor multi-user mobile interaction with a large shared display

When using a mobile device to control a cursor on a large shared display, the interaction must be carefully planned to match the environment and purpose of the systems use. We describe a ‘democratic jukebox’ system that revealed five recommendations that should be considered when designing this type of interaction relating to providing feedback to the user; how to represent users in a multi-cursor based system; where people tend to look and their expectation of how to move their cursor; the orientation of screens and the social context; and, the use of simulated users to give the real users a sense that they are engaging with a greater audience.

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.

Using advanced traits of passengers to facilitate route-choice decision-making

Research interest in pedestrian behaviour spans the retail industry, emergency services, urban planners and other agencies. Most models to simulate and model pedestrian movement can be distinguished on the basis of geographical scale, from the micro-scale movement of obstacle avoidance, through the meso-scale of individuals planning multi-stop shopping trips, up to the macro-scale of overall flow of masses of people between places. In this paper, route-choice decision-making model is devised for modelling passengers flow in airport terminal. A set of devised advanced traits of passengers is firstly proposed. Advanced traits take into account a passenger’s cognitive preferences and demonstrate underlying motivations of route-choice decisions. Although the activities of passengers are normally regarded as stochastic and sometimes unpredictable, real scenarios of passenger flows are basically feasible to be compared with virtual simulations in terms of tactical route-choice decision-making. Passengers in the model are as intelligent agents who possess a bunch of initial basic traits and are categorized into five distinguish groups in terms of routing preferences. Route choices are consecutively determined by inferring current advanced traits according to the utility matrix.

Encouraging learners to drive using game elements and smartphones

Young drivers aged 17-24 years are at a risk of death and injury from road crashes primarily due to their age and inexperience on the road. Our research aims to investigate if a gamified mobile tracking and intervention tool can help to address this issue. We aim to build a smartphone application to support the current process of logging driving hours using a physical logbook and pen in Queensland. This provides an easier way to log driving hours than recording them in a logbook. In an attempt to engage Learners and encourage them to undertake more diverse driving practice we will explore how game elements can be integrated into the experience to motivate Learners. Previous research in other domains has shown that framing tasks as game-like can help engage and motivate users, however the addition of game elements to this space provides some interesting design challenges. This paper presents an overview of the research and presents these challenges for further discussion.

Learning and assessment in Australia

Camp Kilda (CK) is regarded as being a quality early childhood center, and has many features you would typically expect to see in settings across Australia. The children are busily engaged in hands-on activity, playing indoors and outdoors, in the sandpit, under the shade of a big mango tree. The learning environment is planned to offer a variety of activities, including dramatic play, climbing equipment, balls, painting, drawing, clay, books, blocks, writing materials, scissors, manipulative materials. The children are free to access all the materials, and they play either individually or in small groups. The teachers encourage and stimulate the children’s learning, through interactions and thoughtful planning. Learning and assessment at CK is embedded within the cultural and social contexts of the children and their community. Children’s learning is made visible through a rich variety of strategies, including recorded observations, work samples, photographs, and other artifacts. Parents are actively encouraged to build on these “stories” of their children. Planning is based around the teachers’ analysis of the information they gather daily as they interact with the children and their families.

Emergent participant interaction

Emergence has the potential to effect complex, creative or open-ended interactions and novel game-play. We report on research into an emergent interactive system. This investigates emergent user behaviors and experience through the creation and evaluation of an interactive system. The system is +-NOW, an augmented reality, tangible, interactive art system. The paper briefly describes the qualities of emergence and +-NOW before focusing on its evaluation. This was a qualitative study with 30 participants conducted in context. Data analysis followed Grounded Theory Methods. Coding schemes, induced from data and external literature are presented. Findings show that emergence occurred in over half of the participants. The nature of these emergent behaviors is discussed along with examples from the data. Other findings indicate that participants found interaction with the work satisfactory. Design strategies for facilitating satisfactory experience despite the often unpredictable character of emergence, are briefly reviewed and potential application areas for emergence are discussed.