Eight weeks of episodic visual navigation inside a non-stationary environment using adaptive spherical views

This paper presents a long-term experiment where a mobile robot uses adaptive spherical views to localize itself and navigate inside a non-stationary office environment. The office contains seven members of staff and experiences a continuous change in its appearance over time due to their daily activities. The experiment runs as an episodic navigation task in the office over a period of eight weeks. The spherical views are stored in the nodes of a pose graph and they are updated in response to the changes in the environment. The updating mechanism is inspired by the concepts of long- and short-term memories. The experimental evaluation is done using three performance metrics which evaluate the quality of both the adaptive spherical views and the navigation over time.

Pupil shape as viewed along the horizontal visual field

Purpose: Changes in pupil size and shape are relevant for peripheral imagery by affecting aberrations and how much light enters and/or exits the eye. The purpose of this study is to model the pattern of pupil shape across the complete horizontal visual field and to show how the pattern is influenced by refractive error. Methods: Right eyes of thirty participants were dilated with 1% cyclopentolate and images were captured using a modified COAS-HD aberrometer alignment camera along the horizontal visual field to ±90°. A two lens relay system enabled fixation at targets mounted on the wall 3m from the eye. Participants placed their heads on a rotatable chin rest and eye rotations were kept to less than 30°. Best-fit elliptical dimensions of pupils were determined. Ratios of minimum to maximum axis diameters were plotted against visual field angle. Results: Participants’ data were well fitted by cosine functions, with maxima at (–)1° to (–)9° in the temporal visual field and widths 9% to 15% greater than predicted by the cosine of the field angle . Mean functions were 0.99cos[( + 5.3)/1.121], R2 0.99 for the whole group and 0.99cos[( + 6.2)/1.126], R2 0.99 for the 13 emmetropes. The function peak became less temporal, and the width became smaller, with increase in myopia. Conclusion: Off-axis pupil shape changes are well described by a cosine function which is both decentered by a few degrees and flatter by about 12% than the cosine of the viewing angle, with minor influences of refraction.

A reciprocal collaborative method using relevance feedback and feature importance

In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.

Improved line tracker using IMU and vision for visual servoing

This paper introduces an improved line tracker using IMU and vision data for visual servoing tasks. We utilize an Image Jacobian which describes motion of a line feature to corresponding camera movements. These camera motions are estimated using an IMU. We demonstrate impacts of the proposed method in challenging environments: maximum angular rate ~160 0/s, acceleration ~6m /s2 and in cluttered outdoor scenes. Simulation and quantitative tracking performance comparison with the Visual Servoing Platform (ViSP) are also presented.

Towards condition-invariant, top-down visual place recognition

In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.

Objectifying the Subjective : Assessment and Feedback in Creative Arts Studio Learning and Teaching

This paper examines the Assessment and Feedback aspects of Studio Teaching as Creative Arts pedagogy. Prompted by USQ’s newly offered Bachelor of Creative Arts (BCA), the author has developed an Assessment Matrix specifically designed to satisfy a number of imperatives, including: • ‘objectifying’ the subjective aspects of creative practice as assessable coursework/research • providing the means by which accurate, detailed, personalised and confidential feedback may be provided to students individually • providing consistent, accurate, meaningful assessment records for student, lecturer, and institution • ensuring consistency, continuity, and transparency of assessment processes and records to satisfy quality audits • minimising marking and assessment time, whilst maximising assessment integrity and depth • requiring only basic level skills and knowledge of a computer application already in common use (Microsoft Excel) • adaptability to a range of creative courses ‐ across disciplines This Assessment Matrix has been in development (and trialled) since January 2009.

A high performance feedback active noise control system

In many active noise control (ANC) applications, an online secondary path modelling method that uses a white noise as a training signal is required. This paper proposes a new feedback ANC system. Here we modified both the FxLMS and the VSS-LMS algorithms to raised noise attenuation and modelling accuracy for the overall system. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Preventing continuous injection of the white noise increases the performance of the proposed method significantly and makes it more desirable for practical ANC systems. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

Motivating domestic energy conservation through comparative feedback in mobile applications and social networking sites

The progress of technology has led to the increased adoption of energy monitors among household energy consumers. While the monitors available on the market deliver real-time energy usage feedback to the consumer, the form of this data is usually unengaging and mundane. Moreover, it fails to address consumers with different motivations and needs to save and compare energy. This master‟s thesis project presents a study that seeks to inform design guidelines for differently motivated energy consumers. The focus of the research is on comparative feedback supported by a community of energy consumers. In particular, the discussed comparative feedback types are explanatory comparison, temporal self-comparison, norm comparison, one-on-one comparison and ranking, whereby the last three support exploring the potential of socialising energy-related feedback in social networking sites, such as Facebook. These feedback types were integrated in EnergyWiz – a mobile application that enables users to compare with their past performance, neighbours, contacts from social networking sites and other EnergyWiz users. The application was developed through a theory-driven approach and evaluated in personal, semi-structured interviews which provided insights on how motivation-related comparative feedback should be designed. It was also employed in expert focus group discussions which resulted in defining opportunities and challenges before mobile, social energy monitors. The findings have unequivocally shown that users with different motivations to compare and to conserve energy have different preferences for comparative feedback types and design. It was established that one of the most influential factors determining design factors is the people users compare to. In addition, the research found that even simple communication strategies in Facebook, such as wall posts and groups can contribute to engagement with energy conservation practices. The concept of mobility of the application was evaluated as positive since it provides place and time-independent access to the energy consumption data.

Too many cooks? Co-creating and co-teaching studio courses in the creative media context : a career-focussed approach

This Case Study relates to the creation and implementation of career‐focussed courses in Creative Media for film, television, animation, broadcast and web contexts. The paper examines the advantages and disadvantages of co‐teaching, and how different professional and academic backgrounds and disciplines can productively inform curriculum design and delivery in the academic/professional context. The authors, as co‐creators and co‐lecturers, have developed a number of courses which represent current working models for intermediate to advanced level academic/professional study, and attract students from across the creative disciplines; including theatre, media, visual arts and music. These courses are structured to develop in students a wide range of aesthetic and technical skills, as well as their ability to apply those skills professionally within and across the creative media industries. Issues regarding the balance between academic rigour, practical hands‐on skill development, assessment, logistics, resources, teamwork and other issues, are examined in the paper.

Digital beings : an opportunity for Australian visual effects

Ongoing innovation in digital animation and visual effects technologies has provided new opportunities for stories to be visually rendered in ways never before possible. Films featuring animation and visual effects continue to perform well at the box office, proving to be highly profitable projects. The Avengers (Whedon, 2012) holds the current record for opening weekend sales, accruing as much as $207,438,708 USD and $623,357,910 USD gross at time of writing. Life of Pi (Lee, 2012) at time of writing has grossed as much as $608,791,063 USD (Box Office Mojo, 2013). With so much creative potential and a demonstrable ability to generate a large amount of revenue, the animation and visual effects industry – otherwise known as the Post, Digital and Visual Effects (PDV) industry – has become significant to the future growth and stability of the Australian film industry as a whole.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Perception Quality Evaluation with Visual and Infrared Cameras in Challenging Environmental Conditions

This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.

Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).

Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

Towards discrimination of challenging conditions for UGVs with visual and infrared sensors

This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.