707 resultados para Active appearance models


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This thesis presents a novel approach to mobile robot navigation using visual information towards the goal of long-term autonomy. A novel concept of a continuous appearance-based trajectory is proposed in order to solve the limitations of previous robot navigation systems, and two new algorithms for mobile robots, CAT-SLAM and CAT-Graph, are presented and evaluated. These algorithms yield performance exceeding state-of-the-art methods on public benchmark datasets and large-scale real-world environments, and will help enable widespread use of mobile robots in everyday applications.

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The huge amount of CCTV footage available makes it very burdensome to process these videos manually through human operators. This has made automated processing of video footage through computer vision technologies necessary. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned ‘normal’ model. There is no precise and exact definition for an abnormal activity; it is dependent on the context of the scene. Hence there is a requirement for different feature sets to detect different kinds of abnormal activities. In this work we evaluate the performance of different state of the art features to detect the presence of the abnormal objects in the scene. These include optical flow vectors to detect motion related anomalies, textures of optical flow and image textures to detect the presence of abnormal objects. These extracted features in different combinations are modeled using different state of the art models such as Gaussian mixture model(GMM) and Semi- 2D Hidden Markov model(HMM) to analyse the performances. Further we apply perspective normalization to the extracted features to compensate for perspective distortion due to the distance between the camera and objects of consideration. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

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Since its launch in 2006, Twitter has turned from a niche service to a mass phenomenon. By the beginning of 2013, the platform claims to have more than 200 million active users, who “post over 400 million tweets per day” (Twitter, 2013). Its success is spreading globally; Twitter is now available in 33 different languages, and has significantly increased its support for languages that use non-Latin character sets. While Twitter, Inc. has occasionally changed the appearance of the service and added new features—often in reaction to users’ developing their own conventions, such as adding ‘#’ in front of important keywords to tag them—the basic idea behind the service has stayed the same: users may post short messages (tweets) of up to 140 characters and follow the updates posted by other users. This leads to the formation of complex follower networks with unidirectional as well as bidirectional connections between individuals, but also between media outlets, NGOs, and other organisations. While originally ‘microblogs’ were perceived as a new genre of online communication, of which Twitter was just one exemplar, the platform has become synonymous with microblogging in most countries. A notable exception is Sina Weibo, popular in China where Twitter is not available. Other similar platforms have been shut down (e.g., Jaiku), or are being used in slightly different ways (e.g., Tumblr), thus making Twitter a unique service within the social media landscape.

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In outdoor environments shadows are common. These typically strong visual features cause considerable change in the appearance of a place, and therefore confound vision-based localisation approaches. In this paper we describe how to convert a colour image of the scene to a greyscale invariant image where pixel values are a function of underlying material property not lighting. We summarise the theory of shadow invariant images and discuss the modelling and calibration issues which are important for non-ideal off-the-shelf colour cameras. We evaluate the technique with a commonly used robotic camera and an autonomous car operating in an outdoor environment, and show that it can outperform the use of ordinary greyscale images for the task of visual localisation.

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The diverse needs of children have been drawing global attention from both academic and practitioner communities. Based on semi-structured interviews with 23 kin caregivers and five school personnel in the Shijiapu Town of Jilin Province, China, this paper presents a needs model for rural school-age children left behind by their migrant parents. This Chinese model is compared to the needs identification mechanism developed by the Australian Research Alliance for Children and youth. The paper outlines the common needs of children in different contexts, and also highlights the needs that are not explicit in the Australian Research Alliance for Children and Youth framework, such as empowerment and agency or perhaps given insufficient weight, such as education. In discussing relationships among different needs, aspects that are missing in the framework it is argued that culture should be more explicitly recognised when defining need.

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Quality of experience (QoE) measures the overall perceived quality of mobile video delivery from subjective user experience and objective system performance. Current QoE computing models have two main limitations: 1) insufficient consideration of the factors influencing QoE, and; 2) limited studies on QoE models for acceptability prediction. In this paper, a set of novel acceptability-based QoE models, denoted as A-QoE, is proposed based on the results of comprehensive user studies on subjective quality acceptance assessments. The models are able to predict users’ acceptability and pleasantness in various mobile video usage scenarios. Statistical regression analysis has been used to build the models with a group of influencing factors as independent predictors, including encoding parameters and bitrate, video content characteristics, and mobile device display resolution. The performance of the proposed A-QoE models has been compared with three well-known objective Video Quality Assessment metrics: PSNR, SSIM and VQM. The proposed A-QoE models have high prediction accuracy and usage flexibility. Future user-centred mobile video delivery systems can benefit from applying the proposed QoE-based management to optimize video coding and quality delivery decisions.

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Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

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An important aspect of robotic path planning for is ensuring that the vehicle is in the best location to collect the data necessary for the problem at hand. Given that features of interest are dynamic and move with oceanic currents, vehicle speed is an important factor in any planning exercises to ensure vehicles are at the right place at the right time. Here, we examine different Gaussian process models to find a suitable predictive kinematic model that enable the speed of an underactuated, autonomous surface vehicle to be accurately predicted given a set of input environmental parameters.

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Objective To identify predictors for initiating and maintaining active commuting (AC) to work following the 2003 Australia's Walk to Work Day (WTWD) campaign. Methods Pre- and post-campaign telephone surveys of a cohort of working age (18–65years) adults (n = 1100, 55% response rate). Two dependent campaign outcomes were assessed: initiating or maintaining AC (i.e., walk/cycle and public transport) on a single day (WTWD), and increasing or maintaining health-enhancing active commuting (HEAC) level (≥ 30min/day) in a usual week following WTWD campaign. Results A significant population-level increase in HEAC (3.9%) was observed (McNemar's χ2 = 6.53, p = 0.01) with 136 (19.0%) achieving HEAC at post campaign. High confidence in incorporating walking into commute, being active pre-campaign and younger age (< 46years) were positively associated with both outcomes. The utility of AC for avoiding parking hassles (AOR = 2.1, 95% CI: 1.2–3.6), for less expense (AOR = 1.8, 95% CI: 1.1–3.1), for increasing one's health (AOR = 2.5, 95% CI: 1.1–5.6) and for clean air (AOR = 2.2, 95% CI: 1.0–4.4) predicted HEAC outcome whereas avoiding the stress of driving (AOR = 2.6, 95% CI: 1.4–5.0) and the hassle of parking predicted the single-day AC. Conclusions Transportation interventions targeting parking and costs could be further enhanced by emphasizing health benefits of AC. AC was less likely to occur among inactive employees.

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Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, which has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering is rarely known. Patterns are always thought to be more representative than single terms for representing documents. In this paper, a novel information filtering model, Pattern-based Topic Model(PBTM) , is proposed to represent the text documents not only using the topic distributions at general level but also using semantic pattern representations at detailed specific level, both of which contribute to the accurate document representation and document relevance ranking. Extensive experiments are conducted to evaluate the effectiveness of PBTM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model achieves outstanding performance.

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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.

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Mesoporous titania microspheres composed of nanosheets with exposed active facets were prepared by hydrothermal synthesis in the presence of hexafluorosilicic acid. They exhibited superior catalytic activity in the solvent-free synthesis of azoxybenzene by oxidation of aniline and could be used for 7 cycles with slight loss of activity.

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BACKGROUND: Physical activity, particularly walking, is greatly beneficial to health; yet a sizeable proportion of older adults are insufficiently active. The importance of built environment attributes for walking is known, but few studies of older adults have examined neighbourhood destinations and none have investigated access to specific, objectively-measured commercial destinations and walking. METHODS: We undertook a secondary analysis of data from the Western Australian state government's health surveillance survey for those aged 65--84 years and living in the Perth metropolitan region from 2003--2009 (n = 2,918). Individual-level road network service areas were generated at 400 m and 800 m distances, and the presence or absence of six commercial destination types within the neighbourhood service areas identified (food retail, general retail, medical care services, financial services, general services, and social infrastructure). Adjusted logistic regression models examined access to and mix of commercial destination types within neighbourhoods for associations with self-reported walking behaviour. RESULTS: On average, the sample was aged 72.9 years (SD = 5.4), and was predominantly female (55.9%) and married (62.0%). Overall, 66.2% reported some weekly walking and 30.8% reported sufficient walking (>=150 min/week). Older adults with access to general services within 400 m (OR = 1.33, 95% CI = 1.07-1.66) and 800 m (OR = 1.20, 95% CI = 1.02-1.42), and social infrastructure within 800 m (OR = 1.19, 95% CI = 1.01-1.40) were more likely to engage in some weekly walking. Access to medical care services within 400 m (OR = 0.77, 95% CI = 0.63-0.93) and 800 m (OR = 0.83, 95% CI = 0.70-0.99) reduced the odds of sufficient walking. Access to food retail, general retail, financial services, and the mix of commercial destination types within the neighbourhood were all unrelated to walking. CONCLUSIONS: The types of neighbourhood commercial destinations that encourage older adults to walk appear to differ slightly from those reported for adult samples. Destinations that facilitate more social interaction, for example eating at a restaurant or church involvement, or provide opportunities for some incidental social contact, for example visiting the pharmacy or hairdresser, were the strongest predictors for walking among seniors in this study. This underscores the importance of planning neighbourhoods with proximate access to social infrastructure, and highlights the need to create residential environments that support activity across the life course.

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This exploratory enquiry employs qualitative methods to advance knowledge and understanding of physical environmental attributes related to active living among residents of Australian retirement villages. Six focus groups (n = 51 residents) were held and participants described how their current, and subsequently ideal, retirement village and neighborhood supported active lifestyles. Thematic analysis revealed three key environmental factors associated with active living: a positive social environment within the village; services and facilities provided in the village and wider neighborhood; and the presence of suitable pedestrian infrastructure. The unique discovery that environmental factors of both the retirement village and the surrounding neighborhood were associated with residents’ active living raises many questions for study. Findings informed the development of a survey instrument, and further understanding in this area has the potential to contribute to the design and siting practices of senior housing complexes within neighborhoods.

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This study explored individual, social, and built environmental attributes in and outside of the retirement village setting and associations with various active living outcomes including objectively measured physical activity, specific walking behaviors, and social participation. Residents in Perth, Australia (N = 323), were surveyed on environmental perceptions of the village and surrounding neighborhood, self-reported physical activity, and demographic characteristics and wore accelerometers. Managers (N = 32) were surveyed on village characteristics, and objective neighborhood measures were generated in a Geographic Information System (GIS). Results indicated that built- and social-environmental attributes within and outside of retirement villages were associated with active living among residents; however, salient attributes varied depending on the specific outcome considered. Findings suggest that locating villages close to destinations is important for walking and that locating them close to previous and familiar neighborhoods is important for social participation. Further understanding and consideration into retirement village designs that promote both walking and social participation are needed.