868 resultados para object segmentation


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Stationary processes are random variables whose value is a signal and whose distribution is invariant to translation in the domain of the signal. They are intimately connected to convolution, and therefore to the Fourier transform, since the covariance matrix of a stationary process is a Toeplitz matrix, and Toeplitz matrices are the expression of convolution as a linear operator. This thesis utilises this connection in the study of i) efficient training algorithms for object detection and ii) trajectory-based non-rigid structure-from-motion.

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Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

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We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using dynamic time warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later. We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.

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Several researchers are of the opinion that there are many benefits in using the object-oriented paradigm in information systems development. If the object-oriented paradigm is used, the development of information systems may, for example, be faster and more efficient. On the other hand, there are also several problems with the paradigm. For example, it is often considered complex, it is often difficult to make use of the reuse concept and it is still immature in some areas. Although there are several interesting features in the object-oriented paradigm, there is still little comprehensive knowledge of the benefits and problems associated with it. The objective of the following study was to investigate and to gain more understanding of the benefits and problems of the object-oriented paradigm. A review of previous studies was made and twelve benefits and twelve problems were established. These benefits and problems were then analysed, studied and discussed. Further a survey and some case studies were made in order to get some knowledge on what benefits and problems with the object-oriented paradigm Finnish software companies had experienced. One hundred and four companies answered the survey that was sent to all Finnish software companies with five or more employees. The case studies were made with six large Finnish software companies. The major finding was that Finnish software companies were exceptionally positive towards the object-oriented information systems development and had experienced very few of the proposed problems. Finally two models for further research were developed. The first model presents connections between benefits and the second between problems.

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This paper describes a method of automated segmentation of speech assuming the signal is continuously time varying rather than the traditional short time stationary model. It has been shown that this representation gives comparable if not marginally better results than the other techniques for automated segmentation. A formulation of the 'Bach' (music semitonal) frequency scale filter-bank is proposed. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks considering this model. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. 'Bach' filters are seen to marginally outperform the other filters.

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This correspondence describes a method for automated segmentation of speech. The method proposed in this paper uses a specially designed filter-bank called Bach filter-bank which makes use of 'music' related perception criteria. The speech signal is treated as continuously time varying signal as against a short time stationary model. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. The Bach filters are seen to marginally outperform the other filters.

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The purpose of this study was to deepen the understanding of market segmentation theory by studying the evolution of the concept and by identifying the antecedents and consequences of the theory. The research method was influenced by content analysis and meta-analysis. The evolution of market segmentation theory was studied as a reflection of evolution of marketing theory. According to this study, the theory of market segmentation has its roots in microeconomics and it has been influenced by different disciplines, such as motivation research and buyer behaviour theory. Furthermore, this study suggests that the evolution of market segmentation theory can be divided into four major eras: the era of foundations, development and blossoming, stillness and stagnation, and the era of re-emergence. Market segmentation theory emerged in the mid-1950’s and flourished during the period between mid-1950’s and the late 1970’s. During the 1980’s the theory lost its interest in the scientific community and no significant contributions were made. Now, towards the dawn of the new millennium, new approaches have emerged and market segmentation has gained new attention.

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The aim of this masters thesis was to examine subjective wellbeing and personal happiness. Empirical study of happiness is part of broader wellbeing reseach and is based on an idea that the best experts of personal wellbeing are the individuals themselves. In addition to perceptions of personal happiness, the aim was also to acquire knowledge about personal values and components personal happiness is based on. In this study, moving into certain community and the charesteristics of neigbourhood contributing happiness, were defined to represent these values. The object was, through comparative casestudy, to obtain knowledge about subjective wellbeing of the inviduals in two different residental areas inside metropolitan area of Helsinki. In comparative case study the intention usually is that the examined units represent spesific "cases" from something broader and therefore the results can be somehow generalized. Consequently the chosen cases in this study were selected due to their image of "urban village" and thus the juxtapositioning was constructed between secluded post-suburban village and more heterogeneous urban village better attached to excisting urban structure. The researh questins were formed as follows: Are there any differencies between the areas regarding the components personal happines is based on? Are there any differencies between the areas regarding the level of residents subjective wellbeing? Based on the residents assesments, what are the most important charesteristics of neigbourhood contributing personal happiness? The data used in order to gain aswers to these questions was obtained from internet-based survey questionnaire. Based on the data residents of post-suburban village Sundsberg seem to share highly family oriented set of values and actualizing these values is ensured with high income, wealth and secure work situation. Insteadt in Kumpula the components of happiness seem place more towards learning and personal developement, interesting leisure and hobbies and specially having an influence regarding communal decisions. Conserning subjective wellbeing of residents there can be seen some differencies as well. Personal life is experienced a bit more happier in Sundsberg than in Kumpula. People are more satified with their personal health and job satisfaction in Sundsberg and additionally feelings of loneliness, inadequancy and frustration are bit more common in Kumpula. Regarding the charesteristics of neigbourhood contributing happiness data suggests that key charesteristics of area are peacefulness and safely, good location and connections and proximity of parks and recreational areas. These charesteristics were concidered highly significant in both areas but they were experienced to actualize better in Kumpula. In addition to these components the residents in Kumpula were overall more satisfied with various charecteristics contiburing happiness in their residental area. Besides these attributes mentioned above residents in Kumpula emphasize also some "softer" elements connecting into social, functional and communal side of area. From Sundsberg point of view residental area best contributing happiness is child friendly and safe community based on likeminded people who share the same sosioeconomical situation. The results of this study can be linked back into the society and metropolitan area, which they were chosen from as a cases to be studied. The results can thereby be seen as an example of differentation of conditions of personal happiness between certain population segments. It is possible to detect an spatial dimetion to this process as well and thereby the results suggests that regional segmentation affects between high-ranking residental areas as well. Thereby the results of this reseach contributes to the debate on innovative, diverse and dynamic urban area and as well cohesion of metropolitan area and the society in whole.

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During lightning strike to a tall grounded object (TGO), reflections of current waves are known to occur at either ends of the TGO. These reflection modify the channel current and hence, the lightning electromagnetic fields. This study aims to identify the possible contributing factors to reflection at a TGO-channel junction for the current waves ascending on the TGO. Possible sources of reflection identified are corona sheath and discontinuity of resistance and radius. For analyzing the contribution of corona sheath and discontinuity of resistance at the junction, a macroscopic physical model for the return stroke developed in our earlier work is employed. NEC-2D is used for assessing the contribution of abrupt change in radii at a TGO-channel junction. The wire-cage model adopted for the same is validated using laboratory experiments. Detailed investigation revealed the following. The main contributor for reflection at a TGO-channel junction is the difference between TGO and channel core radii. Also, the discontinuity of resistance at a TGO-channel junction can be of some relevance only for the first microsecond regime. Further, corona sheath does not play any significant role in the reflection.

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We introduce a novel temporal feature of a signal, namely extrema-based signal track length (ESTL) for the problem of speech segmentation. We show that ESTL measure is sensitive to both amplitude and frequency of the signal. The short-time ESTL (ST_ESTL) shows a promising way to capture the significant segments of speech signal, where the segments correspond to acoustic units of speech having distinct temporal waveforms. We compare ESTL based segmentation with ML and STM methods and find that it is as good as spectral feature based segmentation, but with lesser computational complexity.

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Some experimental results on the recognition of three-dimensional wire-frame objects are presented. In order to overcome the limitations of a recent model, which employs radial basis functions-based neural networks, we have proposed a hybrid learning system for object recognition, featuring: an optimization strategy (simulated annealing) in order to avoid local minima of an energy functional; and an appropriate choice of centers of the units. Further, in an attempt to achieve improved generalization ability, and to reduce the time for training, we invoke the principle of self-organization which utilises an unsupervised learning algorithm.