Context as a Service

In the vision of Mark Weiser on ubiquitous computing, computers are disappearing from the focus of the users and are seamlessly interacting with other computers and users in order to provide information and services. This shift of computers away from direct computer interaction requires another way of applications to interact without bothering the user. Context is the information which can be used to characterize the situation of persons, locations, or other objects relevant for the applications. Context-aware applications are capable of monitoring and exploiting knowledge about external operating conditions. These applications can adapt their behaviour based on the retrieved information and thus to replace (at least a certain amount) the missing user interactions. Context awareness can be assumed to be an important ingredient for applications in ubiquitous computing environments. However, context management in ubiquitous computing environments must reflect the specific characteristics of these environments, for example distribution, mobility, resource-constrained devices, and heterogeneity of context sources. Modern mobile devices are equipped with fast processors, sufficient memory, and with several sensors, like Global Positioning System (GPS) sensor, light sensor, or accelerometer. Since many applications in ubiquitous computing environments can exploit context information for enhancing their service to the user, these devices are highly useful for context-aware applications in ubiquitous computing environments. Additionally, context reasoners and external context providers can be incorporated. It is possible that several context sensors, reasoners and context providers offer the same type of information. However, the information providers can differ in quality levels (e.g. accuracy), representations (e.g. position represented in coordinates and as an address) of the offered information, and costs (like battery consumption) for providing the information. In order to simplify the development of context-aware applications, the developers should be able to transparently access context information without bothering with underlying context accessing techniques and distribution aspects. They should rather be able to express which kind of information they require, which quality criteria this information should fulfil, and how much the provision of this information should cost (not only monetary cost but also energy or performance usage). For this purpose, application developers as well as developers of context providers need a common language and vocabulary to specify which information they require respectively they provide. These descriptions respectively criteria have to be matched. For a matching of these descriptions, it is likely that a transformation of the provided information is needed to fulfil the criteria of the context-aware application. As it is possible that more than one provider fulfils the criteria, a selection process is required. In this process the system has to trade off the provided quality of context and required costs of the context provider against the quality of context requested by the context consumer. This selection allows to turn on context sources only if required. Explicitly selecting context services and thereby dynamically activating and deactivating the local context provider has the advantage that also the resource consumption is reduced as especially unused context sensors are deactivated. One promising solution is a middleware providing appropriate support in consideration of the principles of service-oriented computing like loose coupling, abstraction, reusability, or discoverability of context providers. This allows us to abstract context sensors, context reasoners and also external context providers as context services. In this thesis we present our solution consisting of a context model and ontology, a context offer and query language, a comprehensive matching and mediation process and a selection service. Especially the matching and mediation process and the selection service differ from the existing works. The matching and mediation process allows an autonomous establishment of mediation processes in order to transfer information from an offered representation into a requested representation. In difference to other approaches, the selection service selects not only a service for a service request, it rather selects a set of services in order to fulfil all requests which also facilitates the sharing of services. The approach is extensively reviewed regarding the different requirements and a set of demonstrators shows its usability in real-world scenarios.

Organic consumers' attitudes and preferences regarding alternatives to piglet castration without anaesthesia and analgesia in organic farming - an explorative analysis

In Germany and other European countries piglets are routinely castrated in order to avoid the occurrence of boar taint, an off-flavour and off-odour of pork. Sensory perception of boar taint varies; however, it is regarded as very unpleasant by many people. Surgical castration which is an effective means against boar taint has commonly been performed without anaesthesia or analgesia within the piglets’ first seven days of life. Piglet castration without anaesthesia has been heavily criticised, as the assumption that young piglets perceive less pain than older animals cannot be supported by scientific evidence. Consequently, surgical castration is only allowed with anaesthesia and/or analgesia in organic farming throughout the European Union since January 2012. Abandoning piglet castration without pain relief requires the implementation of alternative methods which improve animal welfare while maintaining sensory meat quality. There are three relevant alternatives: castration with anaesthesia and/or analgesia to reduce pain, a vaccination against boar taint (immunocastration) and the fattening of uncastrated male pigs (fattening of boars) combined with measures to reduce and detect boar taint in meat. Consumers’ attitudes and opinions regarding the alternatives are an important factor with regard to the implementation of alternatives, as they are finally supposed to buy the meat. The objective of this dissertation was to explore organic consumers’ attitudes, preferences and willingness-to-pay regarding piglet castration without pain relief and the three alternatives. Important aspects for the evaluation of the alternatives and influencing factors (e.g. information, taste) on preferences and willingness-to-pay should also be identified. In autumn 2009 nine focus group discussions were conducted each followed by a Vickrey auction including a tasting of boar salami. Overall, 89 consumers of organic pork participated in the study. Information on piglet castration and alternatives (in three variants) was provided as a basis for discussion. The focus group data were analysed using qualitative content analysis. In order to compare the focus group results with those from the auctions, an innovative approach applying an adapted scoring model to further analyse the data set was used. The majority of participants were not aware that piglets are castrated without anaesthesia in organic farming. They reacted shocked and disappointed on learning about this practice which did not fit into their image of animal welfare standards in organic farming. Overall, the results show, that for consumers of organic pork castration with anaesthesia and analgesia as well as the fattening of boars may be acceptable alternatives in organic farming. Considering the strong food safety concerns regarding immunocastration, acceptance of this alternative may be questioned. Communication regarding alternatives to piglet castration without anaesthesia and analgesia should take into account that the relevance of the aspects animal welfare, food safety, taste and costs differs between alternatives. Furthermore, it seems advisable not to address an unappetizing topic like piglet castration directly at the point of sale so as not to deter consumers from buying organic pork. The issue of piglet castration demonstrates exemplarily that it is important for the organic sector to implement and maintain high animal welfare standards and communicate them in an appropriate way, thereby trying to prevent strong discrepancies between consumers’ expectations regarding animal husbandry in organic farming and actual conditions. So, disappointment of consumers and a loss of image due to negative reports about animal welfare issues can be avoided.

Generating Compliant Motion of Objects with an Articulated Hand

The flexibility of the robot is the key to its success as a viable aid to production. Flexibility of a robot can be explained in two directions. The first is to increase the physical generality of the robot such that it can be easily reconfigured to handle a wide variety of tasks. The second direction is to increase the ability of the robot to interact with its environment such that tasks can still be successfully completed in the presence of uncertainties. The use of articulated hands are capable of adapting to a wide variety of grasp shapes, hence reducing the need for special tooling. The availability of low mass, high bandwidth points close to the manipulated object also offers significant improvements I the control of fine motions. This thesis provides a framework for using articulated hands to perform local manipulation of objects. N particular, it addresses the issues in effecting compliant motions of objects in Cartesian space. The Stanford/JPL hand is used as an example to illustrate a number of concepts. The examples provide a unified methodology for controlling articulated hands grasping with point contacts. We also present a high-level hand programming system based on the methodologies developed in this thesis. Compliant motion of grasped objects and dexterous manipulations can be easily described in the LISP-based hand programming language.

Analysis and Implementation of Robust Grasping Behaviors

This thesis addresses the problem of developing automatic grasping capabilities for robotic hands. Using a 2-jointed and a 4-jointed nmodel of the hand, we establish the geometric conditions necessary for achieving form closure grasps of cylindrical objects. We then define and show how to construct the grasping pre-image for quasi-static (friction dominated) and zero-G (inertia dominated) motions for sensorless and sensor-driven grasps with and without arm motions. While the approach does not rely on detailed modeling, it is computationally inexpensive, reliable, and easy to implement. Example behaviors were successfully implemented on the Salisbury hand and on a planar 2-fingered, 4 degree-of-freedom hand.

Attentional Selection in Object Recognition

A key problem in object recognition is selection, namely, the problem of identifying regions in an image within which to start the recognition process, ideally by isolating regions that are likely to come from a single object. Such a selection mechanism has been found to be crucial in reducing the combinatorial search involved in the matching stage of object recognition. Even though selection is of help in recognition, it has largely remained unsolved because of the difficulty in isolating regions belonging to objects under complex imaging conditions involving occlusions, changing illumination, and object appearances. This thesis presents a novel approach to the selection problem by proposing a computational model of visual attentional selection as a paradigm for selection in recognition. In particular, it proposes two modes of attentional selection, namely, attracted and pay attention modes as being appropriate for data and model-driven selection in recognition. An implementation of this model has led to new ways of extracting color, texture and line group information in images, and their subsequent use in isolating areas of the scene likely to contain the model object. Among the specific results in this thesis are: a method of specifying color by perceptual color categories for fast color region segmentation and color-based localization of objects, and a result showing that the recognition of texture patterns on model objects is possible under changes in orientation and occlusions without detailed segmentation. The thesis also presents an evaluation of the proposed model by integrating with a 3D from 2D object recognition system and recording the improvement in performance. These results indicate that attentional selection can significantly overcome the computational bottleneck in object recognition, both due to a reduction in the number of features, and due to a reduction in the number of matches during recognition using the information derived during selection. Finally, these studies have revealed a surprising use of selection, namely, in the partial solution of the pose of a 3D object.

Computer Analysis of Visual Properties of Curved Objects

A method is presented for the visual analysis of objects by computer. It is particularly well suited for opaque objects with smoothly curved surfaces. The method extracts information about the object's surface properties, including measures of its specularity, texture, and regularity. It also aids in determining the object's shape. The application of this method to a simple recognition task ??e recognition of fruit ?? discussed. The results on a more complex smoothly curved object, a human face, are also considered.

From First Contact to Close Encounters: A Developmentally Deep Perceptual System for a Humanoid Robot

This thesis presents a perceptual system for a humanoid robot that integrates abilities such as object localization and recognition with the deeper developmental machinery required to forge those competences out of raw physical experiences. It shows that a robotic platform can build up and maintain a system for object localization, segmentation, and recognition, starting from very little. What the robot starts with is a direct solution to achieving figure/ground separation: it simply 'pokes around' in a region of visual ambiguity and watches what happens. If the arm passes through an area, that area is recognized as free space. If the arm collides with an object, causing it to move, the robot can use that motion to segment the object from the background. Once the robot can acquire reliable segmented views of objects, it learns from them, and from then on recognizes and segments those objects without further contact. Both low-level and high-level visual features can also be learned in this way, and examples are presented for both: orientation detection and affordance recognition, respectively. The motivation for this work is simple. Training on large corpora of annotated real-world data has proven crucial for creating robust solutions to perceptual problems such as speech recognition and face detection. But the powerful tools used during training of such systems are typically stripped away at deployment. Ideally they should remain, particularly for unstable tasks such as object detection, where the set of objects needed in a task tomorrow might be different from the set of objects needed today. The key limiting factor is access to training data, but as this thesis shows, that need not be a problem on a robotic platform that can actively probe its environment, and carry out experiments to resolve ambiguity. This work is an instance of a general approach to learning a new perceptual judgment: find special situations in which the perceptual judgment is easy and study these situations to find correlated features that can be observed more generally.

Image-Based View Synthesis

We present a new method for rendering novel images of flexible 3D objects from a small number of example images in correspondence. The strength of the method is the ability to synthesize images whose viewing position is significantly far away from the viewing cone of the example images ("view extrapolation"), yet without ever modeling the 3D structure of the scene. The method relies on synthesizing a chain of "trilinear tensors" that governs the warping function from the example images to the novel image, together with a multi-dimensional interpolation function that synthesizes the non-rigid motions of the viewed object from the virtual camera position. We show that two closely spaced example images alone are sufficient in practice to synthesize a significant viewing cone, thus demonstrating the ability of representing an object by a relatively small number of model images --- for the purpose of cheap and fast viewers that can run on standard hardware.

How are Three-Deminsional Objects Represented in the Brain?

We discuss a variety of object recognition experiments in which human subjects were presented with realistically rendered images of computer-generated three-dimensional objects, with tight control over stimulus shape, surface properties, illumination, and viewpoint, as well as subjects' prior exposure to the stimulus objects. In all experiments recognition performance was: (1) consistently viewpoint dependent; (2) only partially aided by binocular stereo and other depth information, (3) specific to viewpoints that were familiar; (4) systematically disrupted by rotation in depth more than by deforming the two-dimensional images of the stimuli. These results are consistent with recently advanced computational theories of recognition based on view interpolation.

Visual Segmentation without Classification in a Model of the Primary Visual Cortex

Stimuli outside classical receptive fields significantly influence the neurons' activities in primary visual cortex. We propose that such contextual influences are used to segment regions by detecting the breakdown of homogeneity or translation invariance in the input, thus computing global region boundaries using local interactions. This is implemented in a biologically based model of V1, and demonstrated in examples of texture segmentation and figure-ground segregation. By contrast with traditional approaches, segmentation occurs without classification or comparison of features within or between regions and is performed by exactly the same neural circuit responsible for the dual problem of the grouping and enhancement of contours.

Component based recognition of objects in an office environment

We present a component-based approach for recognizing objects under large pose changes. From a set of training images of a given object we extract a large number of components which are clustered based on the similarity of their image features and their locations within the object image. The cluster centers build an initial set of component templates from which we select a subset for the final recognizer. In experiments we evaluate different sizes and types of components and three standard techniques for component selection. The component classifiers are finally compared to global classifiers on a database of four objects.

Innovation typology in tourism

Innovation is a research topic with a broad tradition. However, learning processes, from which innovations emerge, and the dynamics of change and development have traditionally been studied in relation with the manufacturing sector. Moreover, the objects of study have been usually process and tangible product innovations. Although recently researchers have focused their attention in other sectors, more research on service innovation should be carried out. Furthermore, regarding innovation in tourism, there is a need to adapt generic theories to the tourism sector and to contribute with new ideas. In order to find out, which are the origins of innovation processes, it is necessary to look into two fundamental subjects that are inherent to innovation, which are learning and interaction. Both are closely related. The first appears to be an intrinsic condition of individuals. Moreover, it can also be identified in organizations. Thus, learning allows individuals as well as organizations to develop. However, learning and development is not possible without taking the environment into account. Hence, it is necessary that interactions take place between individuals, groups of individuals, organizations, etc. Furthermore, the concept of interaction implies the transfer of knowledge, which is the basis for innovations. The purposes of this master thesis are to study in detail several of these topics and to develop a conceptual framework for the research on innovation in tourism

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm