639 resultados para scene change detection


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This paper introduces the creative work Distracted and discusses conceptual, aesthetic and technical aspects of the work. The work was conceived as a luminous, interactive, computational media installation informed by our interest in the Antarctica. Through the paper we focus on: how the work addresses the themes of climate change and sustainability; how we attempted to work with selected sets of scientific data to evoke the delicate yet extreme nature of the environment and the ways in which ice is a record of the earth’s geological history and recent human impacts; and how the process of making this artwork caused us to reconsider our practices and formulate strategies for redirecting our practice in a manner that addresses the challenges of sustainability.

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Australian Constitutional referendums have been part of the Australian political system since federation. Up to the year 1999 (the time of the last referendum in Australia), constitutional change in Australia does not have a good history of acceptance. Since 1901, there have been 44 proposed constitutional changes with eight gaining the required acceptance according to section 128 of the Australian Constitution. In the modern era since 1967, there have been 20 proposals over seven referendum votes for a total of four changes. Over this same period, there have been 13 federal general elections which have realised change in government just five times. This research examines the electoral behaviour of Australian voters from 1967 to 1999 for each referendum. Party identification has long been a key indicator in general election voting. This research considers whether the dominant theory of voter behaviour in general elections (the Michigan Model) provides a plausible explanation for voting in Australian referendums. In order to explain electoral behaviour in each referendum, this research has utilised available data from the Australian Electoral Commission, the 1996 Australian Bureau of Statistics Census data, and the 1999 Australian Constitutional Referendum Study. This data has provided the necessary variables required to measure the impact of the Michigan Model of voter behaviour. Measurements have been conducted using bivariate and multivariate analyses. Each referendum provides an overview of the events at the time of the referendum as well as the =yes‘ and =no‘ cases at the time each referendum was initiated. Results from this research provide support for the Michigan Model of voter behaviour in Australian referendum voting. This research concludes that party identification, as a key variable of the Michigan Model, shows that voters continue to take their cues for voting from the political party they identify with in Australian referendums. However, the outcome of Australian referendums clearly shows that partisanship is only one of a number of contributory factors in constitutional referendums.

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Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

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Many surveillance applications (object tracking, abandoned object detection) rely on detecting changes in a scene. Foreground segmentation is an effective way to extract the foreground from the scene, but these techniques cannot discriminate between objects that have temporarily stopped and those that are moving. We propose a series of modifications to an existing foreground segmentation system\cite{Butler2003} so that the foreground is further segmented into two or more layers. This yields an active layer of objects currently in motion and a passive layer of objects that have temporarily ceased motion which can itself be decomposed into multiple static layers. We also propose a variable threshold to cope with variable illumination, a feedback mechanism that allows an external process (i.e. surveillance system) to alter the motion detectors state, and a lighting compensation process and a shadow detector to reduce errors caused by lighting inconsistencies. The technique is demonstrated using outdoor surveillance footage, and is shown to be able to effectively deal with real world lighting conditions and overlapping objects.

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Abandoned object detection (AOD) systems are required to run in high traffic situations, with high levels of occlusion. Systems rely on background segmentation techniques to locate abandoned objects, by detecting areas of motion that have stopped. This is often achieved by using a medium term motion detection routine to detect long term changes in the background. When AOD systems are integrated into person tracking system, this often results in two separate motion detectors being used to handle the different requirements. We propose a motion detection system that is capable of detecting medium term motion as well as regular motion. Multiple layers of medium term (static) motion can be detected and segmented. We demonstrate the performance of this motion detection system and as part of an abandoned object detection system.

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Automated crowd counting allows excessive crowding to be detected immediately, without the need for constant human surveillance. Current crowd counting systems are location specific, and for these systems to function properly they must be trained on a large amount of data specific to the target location. As such, configuring multiple systems to use is a tedious and time consuming exercise. We propose a scene invariant crowd counting system which can easily be deployed at a different location to where it was trained. This is achieved using a global scaling factor to relate crowd sizes from one scene to another. We demonstrate that a crowd counting system trained at one viewpoint can achieve a correct classification rate of 90% at a different viewpoint.

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Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

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Social and psychological theories have provided a plethora of evidence showing that the physical difficulty to express appropriate social interactions between drivers expresses itself in aggression, selfish driving and anti-social behaviour. Therefore there is a need to improve interactions between drivers and allow clearer collective decision making between them. Personal characteristics and the driving situations play strong roles in driver’s aggression. Our approach is centered around the driving situation as opposed to focusing on personality characteristics. It examines aggression and manipulates contextual variables such as driver’s eye contact exchanges. This paper presents a new unobtrusive in-vehicle system that aims at communicating drivers’ intentions, elicit social responses and increasing mutual awareness. It uses eye gaze as a social cue to affect collective decision making with the view to contribute to safe driving. The authors used a driving simulator to design a case control experiment in which eye gaze movements are conveyed with an avatar. Participants were asked to drive through different types of intersections. An avatar representing the head of the other driver was displayed and driver behaviour was analysed. Significant eye gaze pattern difference where observed when an avatar was displayed. Drivers cautiously refer to the avatar when information is required on the intention of others (e.g. when they do not have the right of way). The majority of participants reported the perception of “being looked at”. The number of glances and time spent gazing at the avatar did not indicate an unsafe distraction by standards of in-vehicle device ergonomic design. Avatars were visually consulted primarily in less demanding driving situations, which underlines their non-distractive nature.

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Acquiring accurate silhouettes has many applications in computer vision. This is usually done through motion detection, or a simple background subtraction under highly controlled environments (i.e. chroma-key backgrounds). Lighting and contrast issues in typical outdoor or office environments make accurate segmentation very difficult in these scenes. In this paper, gradients are used in conjunction with intensity and colour to provide a robust segmentation of motion, after which graph cuts are utilised to refine the segmentation. The results presented using the ETISEO database demonstrate that an improved segmentation is achieved through the combined use of motion detection and graph cuts, particularly in complex scenes.

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The political challenges impeding the negotiation of a comprehensive multilateral agreement on international climate change have received a great deal of attention. A question that has gone somewhat overlooked is what essential components an effective regulatory scheme to reduce greenhouse gas emissions should contain. The objective of this article is to examine the regulatory architecture of current international arrangements relating to global climate change regulation. A systematic analysis of the structure, substantive composition, and administrative characteristics of the UNFCCC and Kyoto Protocol is undertaken. The analytical standard against which the agreements are examined is whether current international regulatory arrangements satisfy the basic requirements of regulatory coherence. The analysis identifies how the present scheme consists of a complex institutional structure that lacks a substantive regulatory core. The implications of the absence of functional and effective mechanisms to govern greenhouse gas emission reductions are considered in relation to the principles of good regulatory design. This, in turn, provides useful insights into how a better regulatory scheme might be designed.

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Appearance-based mapping and localisation is especially challenging when separate processes of mapping and localisation occur at different times of day. The problem is exacerbated in the outdoors where continuous change in sun angle can drastically affect the appearance of a scene. We confront this challenge by fusing the probabilistic local feature based data association method of FAB-MAP with the pose cell filtering and experience mapping of RatSLAM. We evaluate the effectiveness of our amalgamation of methods using five datasets captured throughout the day from a single camera driven through a network of suburban streets. We show further results when the streets are re-visited three weeks later, and draw conclusions on the value of the system for lifelong mapping.

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The purpose of this study was to describe the teaching and leadership experiences of a science teacher who, as head of department, was preparing to introduce changes in the science department of an independent school in response to the requirements of the new junior science syllabus in Queensland, Australia. This teacher consented to classroom observations and interviews with the researchers where his beliefs about teaching practice and change were explored. Other science teachers at the school also were interviewed about their reactions to the planned changes. Interpretive analysis of the data provides an account of the complex interactions, negotiations, compromises, concessions, and trade-offs faced by the teacher during a period of education reform. Perceived barriers existing within the school that impeded proposed change are identified

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This article has been edited from a transcript of the keynote address to the combined ALEA/MTE National Conference, Hobart, Tasmania, August 2001. In this talk Allan reflects on some of the difficulties facing makers of literacy policy in 'New Times'. His reflections are informed by some important research that is having an impact· on literacy teaching in Australia and he raises various issues, ranging from what he sees as a 'dumbing down' of curriculum, to addressing the needs of'at risk' students, to issues of lifelong education in a rapidly changing world.

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This paper investigates the links between various approaches to managing equity and diversity and their effectiveness in changing the measures of inclusivity of women in organisations as a means of auditing and mapping managing diversity outcomes in Australia. The authors argue that managing diversity is more than changing systems and counting numbers it is also about managing the substantive culture change required in order to achieve inclusivity particularly intercultural inclusivity. Research in one sector of the education industry that investigated the competency skills required for culture change is offered as a model or guide for understanding and reflecting upon intercultural competency and its sequential development.