Modelling human behaviour and event detection from videos

Automatic analysis of human behaviour in large collections of videos is gaining interest, even more so with the advent of file sharing sites such as YouTube. However, challenges still exist owing to several factors such as inter- and intra-class variations, cluttered backgrounds, occlusion, camera motion, scale, view and illumination changes. This research focuses on modelling human behaviour for action recognition in videos. The developed techniques are validated on large scale benchmark datasets and applied on real-world scenarios such as soccer videos. Three major contributions are made. The first contribution is in the area of proper choice of a feature representation for videos. This involved a study of state-of-the-art techniques for action recognition, feature extraction processing and dimensional reduction techniques so as to yield the best performance with optimal computational requirements. Secondly, temporal modelling of human behaviour is performed. This involved frequency analysis and temporal integration of local information in the video frames to yield a temporal feature vector. Current practices mostly average the frame information over an entire video and neglect the temporal order. Lastly, the proposed framework is applied and further adapted to real-world scenario such as soccer videos. A dataset consisting of video sequences depicting events of players falling is created from actual match data to this end and used to experimentally evaluate the proposed framework.

Relative importance of environment, human activity and spatial situation in determining the distribution of terrestrial mammal diversity in Argentina

We recorded the number of terrestrial mammal species in each Argentinian province, and the number of species belonging to particular groups (Marsupialia, Placentaria, and among the latter, Xenarthra, Carnivora, Ungulates and Rodentia). We performed multiple regressions of each group’s SR on environmental, human and spatial variables, to determine the amounts of variation explained by these factors. We then used a variance partitioning procedure to specify which proportion of the variation in SR is explained by each of the three factors exclusively and which proportions are attributable to interactions between factors.

Rilevamento della qualità del manto stradale: un approccio sperimentale tramite Machine Learning

Il riconoscimento delle condizioni del manto stradale partendo esclusivamente dai dati raccolti dallo smartphone di un ciclista a bordo del suo mezzo è un ambito di ricerca finora poco esplorato. Per lo sviluppo di questa tesi è stata sviluppata un'apposita applicazione, che combinata a script Python permette di riconoscere differenti tipologie di asfalto. L’applicazione raccoglie i dati rilevati dai sensori di movimento integrati nello smartphone, che registra i movimenti mentre il ciclista è alla guida del suo mezzo. Lo smartphone è fissato in un apposito holder fissato sul manubrio della bicicletta e registra i dati provenienti da giroscopio, accelerometro e magnetometro. I dati sono memorizzati su file CSV, che sono elaborati fino ad ottenere un unico DataSet contenente tutti i dati raccolti con le features estratte mediante appositi script Python. A ogni record sarà assegnato un cluster deciso in base ai risultati prodotti da K-means, risultati utilizzati in seguito per allenare algoritmi Supervised. Lo scopo degli algoritmi è riconoscere la tipologia di manto stradale partendo da questi dati. Per l’allenamento, il DataSet è stato diviso in due parti: il training set dal quale gli algoritmi imparano a classificare i dati e il test set sul quale gli algoritmi applicano ciò che hanno imparato per dare in output la classificazione che ritengono idonea. Confrontando le previsioni degli algoritmi con quello che i dati effettivamente rappresentano si ottiene la misura dell’accuratezza dell’algoritmo.

Nonlinear analysis of human physical activity patterns in health and disease.

The reliable and objective assessment of chronic disease state has been and still is a very significant challenge in clinical medicine. An essential feature of human behavior related to the health status, the functional capacity, and the quality of life is the physical activity during daily life. A common way to assess physical activity is to measure the quantity of body movement. Since human activity is controlled by various factors both extrinsic and intrinsic to the body, quantitative parameters only provide a partial assessment and do not allow for a clear distinction between normal and abnormal activity. In this paper, we propose a methodology for the analysis of human activity pattern based on the definition of different physical activity time series with the appropriate analysis methods. The temporal pattern of postures, movements, and transitions between postures was quantified using fractal analysis and symbolic dynamics statistics. The derived nonlinear metrics were able to discriminate patterns of daily activity generated from healthy and chronic pain states.

A Novel Prediction Method for Early Recognition of Global Human Behaviour in Image Sequences

Human behaviour recognition has been, and still remains, a challenging problem that involves different areas of computational intelligence. The automated understanding of people activities from video sequences is an open research topic in which the computer vision and pattern recognition areas have made big efforts. In this paper, the problem is studied from a prediction point of view. We propose a novel method able to early detect behaviour using a small portion of the input, in addition to the capabilities of it to predict behaviour from new inputs. Specifically, we propose a predictive method based on a simple representation of trajectories of a person in the scene which allows a high level understanding of the global human behaviour. The representation of the trajectory is used as a descriptor of the activity of the individual. The descriptors are used as a cue of a classification stage for pattern recognition purposes. Classifiers are trained using the trajectory representation of the complete sequence. However, partial sequences are processed to evaluate the early prediction capabilities having a specific observation time of the scene. The experiments have been carried out using the three different dataset of the CAVIAR database taken into account the behaviour of an individual. Additionally, different classic classifiers have been used for experimentation in order to evaluate the robustness of the proposal. Results confirm the high accuracy of the proposal on the early recognition of people behaviours.

A survey of human motion analysis using depth imagery

Analysis of human behaviour through visual information has been a highly active research topic in the computer vision community. This was previously achieved via images from a conventional camera, but recently depth sensors have made a new type of data available. This survey starts by explaining the advantages of depth imagery, then describes the new sensors that are available to obtain it. In particular, the Microsoft Kinect has made high-resolution real-time depth cheaply available. The main published research on the use of depth imagery for analysing human activity is reviewed. Much of the existing work focuses on body part detection and pose estimation. A growing research area addresses the recognition of human actions. The publicly available datasets that include depth imagery are listed, as are the software libraries that can acquire it from a sensor. This survey concludes by summarising the current state of work on this topic, and pointing out promising future research directions.

Deep learning architecture for gesture recognition

Pós-graduação em Engenharia Mecânica - FEG

Human MutSalpha recognizes damaged DNA base pairs containing O6-methylguanine, O4-methylthymine, or the cisplatin-d(GpG) adduct.

Bacterial and mammalian mismatch repair systems have been implicated in the cellular response to certain types of DNA damage, and genetic defects in this pathway are known to confer resistance to the cytotoxic effects of DNA-methylating agents. Such observations suggest that in addition to their ability to recognize DNA base-pairing errors, members of the MutS family may also respond to genetic lesions produced by DNA damage. We show that the human mismatch recognition activity MutSalpha recognizes several types of DNA lesion including the 1,2-intrastrand d(GpG) crosslink produced by cis-diamminedichloroplatinum(II), as well as base pairs between O6-methylguanine and thymine or cytosine, or between O4-methylthymine and adenine. However, the protein fails to recognize 1,3-intrastrand adduct produced by trans-diamminedichloroplatinum(II) at a d(GpTpG) sequence. These observations imply direct involvement of the mismatch repair system in the cytotoxic effects of DNA-methylating agents and suggest that recognition of 1,2-intrastrand cis-diamminedichloroplatinum(II) adducts by MutSalpha may be involved in the cytotoxic action of this chemotherapeutic agent.

An activity theory approach to strategy as practice

This chapter introduces activity theory as an approach for studying strategy as practice. Activity theory conceptualizes the ongoing construction of activity as a product of activity systems, comprising the actor, the community with which that actor interacts and those symbolic and material tools that mediate between actors, their community and their pursuit of activity. The focus on the mediating role of tools and cultural artefacts in human activity seems especially promising for advancing the strategy-as-practice agenda, for example as a theoretical resource for the growing interest in sociomateriality and the role of tools and artefacts in (strategy) practice (for example, Balogun et al. 2014; Lanzara 2009; Nicolini 2009; Spee and Jarzabkowski 2009; Stetsenko 2005). Despite its potential, in a recent review Vaara and Whittington (2012) identified only three strategy-as-practice articles explicitly applying an activity theory lens. In the wider area of practice-based studies in organizations, activity theory has been slightly more popular (for example, Blackler 1993; 1995; Blackler, Crump and McDonald 2000; Engeström, Kerosuo and Kajamaa 2007; Groleau 2006; Holt 2008; Miettinen and Virkkunen 2005). It still lags behind its potential, however, primarily because of its origins as a social psychology theory developed in Russia with little initial recognition outside the Russian context, particularly in the area of strategy and organization theory, until recently (Miettinen, Samra-Fredericks and Yanow 2009). This chapter explores activity theory as a resource for studying strategy as practice as it is socially accomplished by individuals in interaction with their wider social group and the artefacts of interaction. In particular, activity theory’s focus on actors as social individuals provides a conceptual basis for studying the core question in strategy-as-practice research: what strategy practitioners do. The chapter is structured in three parts. First, an overview of activity theory is provided. Second, activity theory as a practice-based approach to studying organizational action is introduced and an activity system conceptual framework is developed. Third, the elements of the activity system are explained in more detail and explicitly linked to each of the core SAP concepts: practitioners, practices and praxis. In doing so, links are made to existing strategy-as-practice research, with brief empirical examples of topics that might be addressed using activity theory. Throughout the chapter, we introduce key authors in the development of activity theory and its use in management and adjacent disciplinary fields, as further resources for those wishing to make greater use of activity theory.

Human settlements: Australia state of the environment report, 2001

Australia’s transition to the 21st century has been marked by an extended period of economic prosperity unmatched for several decades, but one in which a series of question marks are being raised in three principal areas: in relation to the environment, the social well-being of the population, and the future path of economic development. The first concern, which is of primary interest in this report, relates to the physical environment of cities and their surrounding regions, and the range of pressures exerted by population and human activity. The report begins by noting the increasing divergence of the prime indicator of national economic performance—gross domestic product (GDP)—from the Genuine Progress Indicator (GPI). GPI is a new experimental measure of sustainable development that accommodates factors currently unaccounted for in GDP, such as income distribution, value of household work, cost of unemployment, and various other social and environmental costs. The divergence of these two indicators in recent decades suggests that Australia’s growth has been heavily dependent on the draw-down of the nation’s stocks of capital assets (its infrastructure), its human and social capital, and its natural capital (Hamilton 1997).

Records of predatory, con-specific and human induced mauls on fish from the Northeast Atlantic and Black Sea

Present study aims to describe records of mauled and con-specific injures in various fish inhabiting different environment and to discuss possible impacts on fish behavior and ontogenesis. The fish specimens were collected from the Black Sea and Azores Islands (NE Atlantic). Individuals of European flounder, Pleuronectes flesus, common stingray, Dasyatis pastinaca and turbot, Scophthalmus maximus with missing dorsal and caudal fins and flesh, were found in the Black Sea. Specimens with severe mauls of the ocean sunfish, Mola mola, almaco jack, Seriola rivoliana and sargo, Diplodus sargus were recorded from the Azores Islands. All of them were caught alive and survived severe mauls caused by predators or by accidents with propellers, fishing nets. The NE Atlantic records, although possibly caused by natural predation, are more probably than not the result of negative interactions with human activity. Numerous records of mauled fish species from both regions show that the problem with adverse effects of fisheries is quite important. Predatory and con-specific injuries obviously are compatible with basic fish vital functions of described cases. The problem with negative anthropogenic interactions seems to be insufficiently investigated and need more attention by responsible managers and decision makers.

A percepção dos profissionais de saúde sobre o trabalho em equipa no contexto do Hospital do Espírito Santo de Évora, E.P.E.

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde

Development and efficiency optimizing of the human body energy converters

Nowadays it is known that the human body is continuous source of many types of energy and the devices used for collecting energy taken from the environment also have the required capabilities for the collection of the energy produced by the Human body (HB), but very limited and with very low efficiency. Low power and high yield converters are particularly needed in these cases of collecting energy from human activity and its movements due to the small amount of energy generated this way. But this situation can be improved. Enhancing or focusing the human movements by using mechanical amplifiers applied to the piezoelectric element. By doing so the input of energy in the element increases. As such increasing its output, therefore producing more energy.

Sandfly species diversity in association with human activities in the Kani tribe settlements of the Western Ghats, Thiruvananthapuram, Kerala, India

Sandfly prevalence in the Kani tribe settlements of Western Ghats in India was investigated. A total of 1,279 sandflies comprising 17 species was obtained. Sandfly abundance showed a negative correlation (r = -0.97, p = 0.003) with increase in altitudinal ranges from 0-1,000 m. When sandfly samples were grouped according to landscape characteristics of the location, the estimated Shannon-Weiner index (H) and species richness index (S) were high and species evenness index (J) was low in settlements located at 0-300 m altitudinal range. On the contrary, the values of H and J were high, while S was low at 301-600 m altitudinal range. With further increase in altitude, species diversity, S and J were low. Though the relative abundance of sandflies decreased with increase in altitude, the influence of altitudinal variation could not be attributed to determine sandfly diversity, since the number of sampling units were not uniform at all the altitudinal gradients due to nonavailability of suitable resting shelters. Sandfly species showed great aggregation at 0-300 m altitude interval, where not only the number of settlements were maximum (n = 19), but also the environmental conditions favoured sandfly abundance due to the concentration of tribal settlements, human dwellings and his activities.