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This paper introduces Vocville, a causal online game for learning vocabularies. I am creating this application for my master thesis of my career as a "Computervisualist" (computer visions) for the University of Koblenz - Landau. The application is an online browser game based on the idea of the really successful Facebook game FarmVille. The application is seperated in two parts; a Grails application manages a database which holds the game objects like vocabulary, a Flex/Flash application generates the actual game by using these data. The user can create his own home with everything in it. For creating things, the user has to give the correct translation of the object he wants to create several times. After every query he has to wait a certain amount of time to be queried again. When the correct answer is given sufficient times, the object is builded. After building one object the user is allowed to build others. After building enough objects in one area (i.e. a room, a street etc.) the user can activate other areas by translating all the vocabularies of the previous area. Users can also interact with other users by adding them as neighbors and then visiting their homes or sending them gifts, for which they have to fill in the correct word in a given sentence.
This thesis evaluates automated techniques to remove objects from an image and proposed several modifications for the specific application of removing a colour checker from structure dominated images. The selection of approaches covers the main research field of image inpainting as well as an approach used in medical image processing. Their results are investigated to disclose their applicability to removing objects from structure-intense images. The advantages and disadvantages discovered in the process are then used to propose several modifications for an adapted inpainting approach suitable for removing the colour checker.
The automatic detection of position and orientation of subsea cables and pipelines in camera images enables underwater vehicles to make autonomous inspections. Plants like algae growing on top and nearby cables and pipelines however complicate their visual detection: the determination of the position via border detection followed by line extraction often fails. Probabilistic approaches are here superior to deterministic approaches. Through modeling probabilities it is possible to make assumptions on the state of the system even if the number of extracted features is small. This work introduces a new tracking system for cable/pipeline following in image sequences which is based on particle filters. Extensive experiments on realistic underwater videos show robustness and performance of this approach and demonstrate advantages over previous works.
Research has shown that people recognize personality, gender, inner states and many other items of information by simply observing human motion. Therefore the expressive human motion seems to be a valuable non-verbal communication channel. On the quest for more believable characters in virtual three dimensional simulations a great amount of visual realism has been achieved during the last decades. However, while interacting with synthetic characters in real-time simulations, often human users still sense an unnatural stiffness. This disturbance in believability is generally caused by a lack of human behavior simulation. Expressive motions, which convey personality and emotional states can be of great help to create more plausible and life-like characters. This thesis explores the feasibility of an automatic generation of emotionally expressive animations from given neutral character motions. Such research is required since common animation methods, such as manual modeling or motion capturing techniques, are too costly to create all possible variations of motions needed for interactive character behavior. To investigate how emotions influence human motion relevant literature from various research fields has been viewed and certain motion rules and features have been extracted. These movement domains were validated in a motion analysis and implemented in a system in an exemplary manner capable of automating the expression of angry, sad and happy states in a virtual character through its body language. Finally, the results were evaluated in user test.