Towards Vision-Based Pose- and Condition-Invariant Place Recognition along Routes

Vision-based place recognition involves recognising familiar places despite changes in environmental conditions or camera viewpoint (pose). Existing training-free methods exhibit excellent invariance to either of these challenges, but not both simultaneously. In this paper, we present a technique for condition-invariant place recognition across large lateral platform pose variance for vehicles or robots travelling along routes. Our approach combines sideways facing cameras with a new multi-scale image comparison technique that generates synthetic views for input into the condition-invariant Sequence Matching Across Route Traversals (SMART) algorithm. We evaluate the system’s performance on multi-lane roads in two different environments across day-night cycles. In the extreme case of day-night place recognition across the entire width of a four-lane-plus-median-strip highway, we demonstrate performance of up to 44% recall at 100% precision, where current state-of-the-art fails.

Unsupervised online learning of condition-invariant images for place recognition

This paper presents an online, unsupervised training algorithm enabling vision-based place recognition across a wide range of changing environmental conditions such as those caused by weather, seasons, and day-night cycles. The technique applies principal component analysis to distinguish between aspects of a location’s appearance that are condition-dependent and those that are condition-invariant. Removing the dimensions associated with environmental conditions produces condition-invariant images that can be used by appearance-based place recognition methods. This approach has a unique benefit – it requires training images from only one type of environmental condition, unlike existing data-driven methods that require training images with labelled frame correspondences from two or more environmental conditions. The method is applied to two benchmark variable condition datasets. Performance is equivalent or superior to the current state of the art despite the lesser training requirements, and is demonstrated to generalise to previously unseen locations.

Financial Reserves : A Necessary Condition for Not-for-Profit Sustainability?

Should not-for-profit (NFP) organisations hold reserves to hedge uncertainty and protect mission delivery? This chapter outlines the nature and contxt of NFP reserves. many would accept that actors within NFP organisations have a broad accountability to ensure sustinability where an appropriate mission exists, and that sustinability is assisted or ensured through the purposeful accumulation of reserves. This chapter examins current relevant literature on reserves, reviews various approaches to reserves accumulation across jurisdictions and reports what is known about practice. We highlight the tension faced by NFP organisations, balancing mission spending against the need to hedge uncertainty. We investigate the role of reserves, and how an appropriate level is determined to ensure a NFP board's accountability for organisational sustinability. This issue is particularly significant in the period following the global financial crisis, and while practitioner interest is evident, there has been little academic attention paid to the topic of NFP reserves, and 'very few [articles] have even forcused on related topics' (Calabrese, 2011, p. 282).

Evaluation of object detection proposals under condition variations

Object detection is a fundamental task in many computer vision applications, therefore the importance of evaluating the quality of object detection is well acknowledged in this domain. This process gives insight into the capabilities of methods in handling environmental changes. In this paper, a new method for object detection is introduced that combines the Selective Search and EdgeBoxes. We tested these three methods under environmental variations. Our experiments demonstrate the outperformance of the combination method under illumination and view point variations.

Place recognition with ConvNet landmarks: Viewpoint-robust, condition-robust, training-free

Place recognition has long been an incompletely solved problem in that all approaches involve significant compromises. Current methods address many but never all of the critical challenges of place recognition – viewpoint-invariance, condition-invariance and minimizing training requirements. Here we present an approach that adapts state-of-the-art object proposal techniques to identify potential landmarks within an image for place recognition. We use the astonishing power of convolutional neural network features to identify matching landmark proposals between images to perform place recognition over extreme appearance and viewpoint variations. Our system does not require any form of training, all components are generic enough to be used off-the-shelf. We present a range of challenging experiments in varied viewpoint and environmental conditions. We demonstrate superior performance to current state-of-the- art techniques. Furthermore, by building on existing and widely used recognition frameworks, this approach provides a highly compatible place recognition system with the potential for easy integration of other techniques such as object detection and semantic scene interpretation.

Daubism: Copyright law and artistic works

An artistic controversy over a group of landscape painters called the Daubists provided impetus for copyright law reform in Australia in the early 1990's. In the first exhibition of Daubism in 1991 driller Jet Armstrong painted a crop circle over a painting of the Olgas by Charles Bannon - an artist, print-maker, and the father of the State Premier at the time, John Bannon. He called the resulting work, Crop Circles on a Bannon Landscape. Armstrong also inserted an inverted crucifix over a painting of the Flinders Ranges by Bannon, and renamed the work The Crop Circle Conspiracy Landscape. In response, Bannon took legal action against Armstrong in the Federal Court of Australia on the grounds of false attribution and defamation. He won an interlocutory injunction against Armstrong and the gallery, but then reached a settlement with the Daubists. An anonymous buyer purchased the work for $650 on the condition that it was returned to the painter. In his fight against the Daubists, Bannon received help and support from the National Association for the Visual Arts (NAVA). This professional group used the controversy to campaign for the reform of copyright law - in particular, the need for a moral rights regime. The artistic controversy over the Daubists was a catalyst for the introduction of the Copyright Amendment (Moral Rights) Act 2000 (Cth) in Australia. It offers an illuminating case study of the operation of copyright law in the visual arts.

Minimising the failure of rail joints through managing the localised condition of track

To effectively address the high rate of failure of Insulated Rail Joints (IRJs) in the heavy haul lines, a research plan was designed and implemented with particular attention to understand their mechanical behaviour and deterioration process. In this paper, part of this ongoing research is described. During the past decades many studies have tried to improve the service life of IRJs by introducing a new structural design or material for IRJ components. This paper looks into this problem from a different perspective highlighting the significance of localised condition of track to the loads and responses of the IRJs. Results from a series of field measurements conducted in a rail track within the Australian Rail Track Corporation (ARTC) network are discussed. The interactive effects of IRJ responses and localised track condition are further investigated using the results obtained from numerical simulations. The field measurements and the simulation results provide valuable insight on the influence of track condition to the behaviour of IRJs.

Comparison of visual inspection and structural-health monitoring as bridge condition assessment methods

This paper presents the results of a research project aimed at examining the capabilities and challenges of two distinct but not mutually exclusive approaches to in-service bridge assessment: visual inspection and installed monitoring systems. In this study, the intended functionality of both approaches was evaluated on its ability to identify potential structural damage and to provide decision-making support. Inspection and monitoring are compared in terms of their functional performance, cost, and barriers (real and perceived) to implementation. Both methods have strengths and weaknesses across the metrics analyzed, and it is likely that a hybrid evaluation technique that adopts both approaches will optimize efficiency of condition assessment and ultimately lead to better decision making.

An investigation of Nano-particle deposition in cylindrical tubes under Laminar condition using Lagrangian transport model

Aerosol deposition in cylindrical tubes is a subject of interest to researchers and engineers in many applications of aerosol physics and metrology. Investigation of nano-particles in different aspects such as lungs, upper airways, batteries and vehicle exhaust gases is vital due the smaller size, adverse health effect and higher trouble for trapping than the micro-particles. The Lagrangian particle tracking provides an effective method for simulating the deposition of nano-particles as well as micro-particles as it accounts for the particle inertia effect as well as the Brownian excitation. However, using the Lagrangian approach for simulating ultrafine particles has been limited due to computational cost and numerical difficulties. In this paper, the deposition of nano-particles in cylindrical tubes under laminar condition is studied using the Lagrangian particle tracking method. The commercial Fluent software is used to simulate the fluid flow in the pipes and to study the deposition and dispersion of nano-particles. Different particle diameters as well as different flow rates are examined. The point analysis in a uniform flow is performed for validating the Brownian motion. The results show good agreement between the calculated deposition efficiency and the analytic correlations in the literature. Furthermore, for the nano-particles with the diameter more than 40 nm, the calculated deposition efficiency by the Lagrangian method is less than the analytic correlations based on Eulerian method due to statistical error or the inertia effect.