Subobject Detection through Spatial Relationships on Mobile Phones

We present a novel image classification technique for detecting multiple objects (called subobjects) in a single image. In addition to image classifiers, we apply spatial relationships among the subobjects to verify and to predict locations of detected and undetected subobjects, respectively. By continuously refining the spatial relationships throughout the detection process, even locations of completely occluded exhibits can be determined. Finally, all detected subobjects are labeled and the user can select the object of interest for retrieving corresponding multimedia information. This approach is applied in the context of PhoneGuide, an adaptive museum guidance system for camera-equipped mobile phones. We show that the recognition of subobjects using spatial relationships is up to 68% faster than related approaches without spatial relationships. Results of a field experiment in a local museum illustrate that unexperienced users reach an average recognition rate for subobjects of 85.6% under realistic conditions

Subobject Detection through Spatial Relationships on Mobile Phones

We present a novel image classification technique for detecting multiple objects (called subobjects) in a single image. In addition to image classifiers, we apply spatial relationships among the subobjects to verify and to predict locations of detected and undetected subobjects, respectively. By continuously refining the spatial relationships throughout the detection process, even locations of completely occluded exhibits can be determined. Finally, all detected subobjects are labeled and the user can select the object of interest for retrieving corresponding multimedia information. This approach is applied in the context of PhoneGuide, an adaptive museum guidance system for camera-equipped mobile phones. We show that the recognition of subobjects using spatial relationships is up to 68% faster than related approaches without spatial relationships. Results of a field experiment in a local museum illustrate that unexperienced users reach an average recognition rate for subobjects of 85.6% under realistic conditions

Adaptive Image Classification on Mobile Phones

The advent of high-performance mobile phones has opened up the opportunity to develop new context-aware applications for everyday life. In particular, applications for context-aware information retrieval in conjunction with image-based object recognition have become a focal area of recent research. In this thesis we introduce an adaptive mobile museum guidance system that allows visitors in a museum to identify exhibits by taking a picture with their mobile phone. Besides approaches to object recognition, we present different adaptation techniques that improve classification performance. After providing a comprehensive background of context-aware mobile information systems in general, we present an on-device object recognition algorithm and show how its classification performance can be improved by capturing multiple images of a single exhibit. To accomplish this, we combine the classification results of the individual pictures and consider the perspective relations among the retrieved database images. In order to identify multiple exhibits in pictures we present an approach that uses the spatial relationships among the objects in images. They make it possible to infer and validate the locations of undetected objects relative to the detected ones and additionally improve classification performance. To cope with environmental influences, we introduce an adaptation technique that establishes ad-hoc wireless networks among the visitors’ mobile devices to exchange classification data. This ensures constant classification rates under varying illumination levels and changing object placement. Finally, in addition to localization using RF-technology, we present an adaptation technique that uses user-generated spatio-temporal pathway data for person movement prediction. Based on the history of previously visited exhibits, the algorithm determines possible future locations and incorporates these predictions into the object classification process. This increases classification performance and offers benefits comparable to traditional localization approaches but without the need for additional hardware. Through multiple field studies and laboratory experiments we demonstrate the benefits of each approach and show how they influence the overall classification rate.Die Einführung von Mobiltelefonen mit eingebauten Sensoren wie Kameras, GPS oder Beschleunigungssensoren, sowie Kommunikationstechniken wie Bluetooth oder WLAN ermöglicht die Entwicklung neuer kontextsensitiver Anwendungen für das tägliche Leben. Insbesondere Applikationen im Bereich kontextsensitiver Informationsbeschaffung in Verbindung mit bildbasierter Objekterkennung sind in den Fokus der aktuellen Forschung geraten. Der Beitrag dieser Arbeit ist die Entwicklung eines bildbasierten, mobilen Museumsführersystems, welches unterschiedliche Adaptionstechniken verwendet, um die Objekterkennung zu verbessern. Es wird gezeigt, wie Ojekterkennungsalgorithmen auf Mobiltelefonen realisiert werden können und wie die Erkennungsrate verbessert wird, indem man zum Beispiel ad-hoc Netzwerke einsetzt oder Bewegungsvorhersagen von Personen berücksichtigt

InContexto: Multisensor Architecture to Obtain People Context from Smartphones

The way users intectact with smartphones is changing after the improvements made in their embedded sensors. Increasingly, these devices are being employed as tools to observe individuals habits. Smartphones provide a great set of embedded sensors, such as accelerometer, digital compass, gyroscope, GPS, microphone, and camera. This paper aims to describe a distributed architecture, called inContexto, to recognize user context information using mobile phones. Moreover, it aims to infer physical actions performed by users such as walking, running, and still. Sensory data is collected by HTC magic application made in Android OS, and it was tested achieving about 97% of accuracy classifying five different actions (still, walking and running).This work was supported in part by Projects CICYT TIN2011-28620-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029- C02-02.Publicad

Configuration management for models : generic methods for model comparison and model co-evolution

It is an undeniable fact that software plays an important role in our lives. We use the software to play our music, to check our e-mail, or even to help us drive our car. Thus, the quality of software directly influences the quality of our lives. However, the traditional Software Engineering paradigm is not able to cope with the increasing demands in quantity and quality of produced software. Thus, a new paradigm of Model Driven Software Engineering (MDSE) is quickly gaining ground. MDSE promises to solve some of the problems of traditional Software Engineering (SE) by raising the level of abstraction. Thus, MDSE proposes the use of models and model transformations, instead of textual program files used in traditional SE, as means of producing software. The models are usually graph-based, and are built by using graphical notations – i.e. the models are represented diagrammatically. The advantages of using graphical models over text files are numerous, for example it is usually easier to deduce the relations between different model elements in their diagrammatic form, thus reducing the possibility of defects during the production of the software. Furthermore, formal model transformations can be used to produce different kinds of artifacts from models in all stages of software production. For example, artifacts that can be used as input for model checkers or simulation tools can be produced. This enables the checking or simulation of software products in the early phases of development, which further reduces the probability of defects in the final software product. However, methods and techniques to support MDSE are still not mature enough. In particular methods and techniques for model configuration management (MCM) are still in development, and no generic MCM system exists. In this thesis, I describe my research which was focused on developing methods and techniques to support generic model configuration management. In particular, during my research, I focused on developing methods and techniques for supporting model evolution and model co-evolution. Described methods and techniques are generic and are suitable for a state-based approach to model configuration management. In order to support the model evolution, I developed methods for the representation, calculation, and visualization of state-based model differences. Unlike in previously published research, where these three aspects of model differences are dealt with in separation, in my research all these three aspects are integrated. Thus, the result of model differences calculation algorithm is in the format which is described by my research on model differences representation. The same representation format of model differences is used as a basis of my approach to differences visualization. It is important to notice that the developed representation format for model differences is metamodel independent, and thus is generic, i.e., it can be used to represent differences between all graph-based models. Model co-evolution is a term that describes the problem of adapting models when their metamodels evolve. My solution to this problem has three steps. In the first step a special metamodel MMfMM is introduced. Unlike in traditional approaches, where metamodels are represented as instances of a metametamodel, in my approach the metamodels are represented by models which are instances of an MMfMM. In the second step, since metamodels are represented by models, previously defined methods and techniques for model evolution are reused to represent and calculate the metamodel differences. In the final step I define an algorithm that uses the calculated metamodel differences to adapt models conforming to the evolved metamodel. In order to validate my approaches to model evolution and model co-evolution, I have developed a tool for comparing models and visualizing resulting differences, and a tool for model co-evolution. Moreover, I have developed a method to compare tools for model comparison, and using this method I have conducted a series of experiments in which I compared the tool I developed to an industrial tool called EMFCompare. The results of these experiments are also presented in the thesis. Furthermore, in order to validate my tool and approach to model co-evolution, I have also specified and conducted several experiments. The results of these experiments are also presented in the thesis

Revisiting Isolation For System Security And Efficiency In The Era Of Internet Of Things

Isolation is a fundamental paradigm for secure and efficient resource sharing on a computer system. However, isolation mechanisms in traditional cloud computing platforms are heavy-weight or just not feasible to be applied onto the computing environment for Internet of Things(IoT). Most IoT devices have limited resources and their servers are less powerful than cloud servers but are widely distributed over the edge of the Internet. Revisions to the traditional isolation mechanisms are needed in order to improve the system security and efficiency in these computing environments. The first project explores container-based isolation for the emerging edge computing platforms. We show a performance issue of live migration between edge servers where the file system transmission becomes a bottleneck. Then we propose a solution that leverages a layered file system for synchronization before the migration starts, avoiding the usage of impractical networking shared file system as in the traditional solution. The evaluation shows that the migration time is reduced by 56% – 80%. In the second project, we propose a lightweight security monitoring service for edge computing platforms, base on the virtual machine isolation technique. Our framework is designed to monitor program activities from underneath of an operating system, which improves its transparency and avoids the cost of embedding different monitor modules into each layer inside the operating system. Furthermore, the monitor runs in a single process virtual machine which requires only ≤32MB of memory, reduces the scheduling overhead, and saves a significant amount of physical memory, while the performance overhead is an average of 2.7%. In the third project, we co-design the hardware and software system stack to achieve efficient fine-grained intra-address space isolation. We propose a systematic solution to partition a legacy program into multiple security compartments, which we call capsules, with isolation at byte granularity. Vulnerabilities in one capsule will not likely affect another capsule. The isolation is guaranteed by our hardware-based ownership types tagged to every byte in the memory. The ownership types are initialized, propagated, and checked by combining both static and dynamic analysis techniques. Finally, our co-design approach could remove most human refactoring efforts while avoiding the untrustworthiness as well as the cost of the pure software approaches. In brief, this proposal explores a spectrum of isolation techniques and their improvementsfor the IoT computing environment. With our explorations, we have shown the necessity to revise the traditional isolation mechanisms in order to improve the system efficiency and security for the edge and IoT platforms. We expect that many more opportunities will be discovered and various kinds of revised or new isolation mechanisms for the edge and IoT platforms will emerge soon

Survivability aspects of future optical backbone networks

In huidige glasvezelnetwerken kan een enkele vezel een gigantische hoeveelheid data dragen, ruwweg het equivalent van 25 miljoen gelijktijdige telefoongesprekken. Hierdoor zullen netwerkstoringen, zoals breuken van een glasvezelkabel, de communicatie van een groot aantal eindgebruikers verstoren. Netwerkoperatoren kiezen er dan ook voor om hun netwerk zo te bouwen dat zulke grote storingen automatisch opgevangen worden. Dit proefschrift spitst zich toe op twee aspecten rond de overleefbaarheid in toekomstige optische netwerken. De eerste doelstelling die beoogd wordt is het tot stand brengen vanrobuuste dataverbindingen over meerdere netwerken. Door voldoende betrouwbare verbindingen tot stand te brengen over een infrastructuur die niet door een enkele entiteit wordt beheerd kan men bv. weredwijd Internettelevisie van hoge kwaliteit aanbieden. De bestudeerde oplossing heeft niet enkel tot doel om deze zeer betrouwbare verbinding te berekenen, maar ook om dit te bewerkstelligen met een minimum aan gebruikte netwerkcapaciteit. De tweede doelstelling was om een antwoord te formuleren om de vraag hoe het toepassen van optische schakelsystemen gebaseerd op herconfigureerbare optische multiplexers een impact heeft op de overleefbaarheid van een optisch netwerk. Bij lagere volumes hebben optisch geschakelde netwerken weinig voordeel van dergelijke gesofistikeerde methoden. Elektronisch geschakelde netwerken vertonen geen afhankelijkheid van het datavolume en hebben altijd baat bij optimalisatie