Activity Analysis; Finding Explanations for Sets of Events

Automatic activity recognition is the computational process of analysing visual input and reasoning about detections to understand the performed events. In all but the simplest scenarios, an activity involves multiple interleaved events, some related and others independent. The activity in a car park or at a playground would typically include many events. This research assumes the possible events and any constraints between the events can be defined for the given scene. Analysing the activity should thus recognise a complete and consistent set of events; this is referred to as a global explanation of the activity. By seeking a global explanation that satisfies the activity’s constraints, infeasible interpretations can be avoided, and ambiguous observations may be resolved. An activity’s events and any natural constraints are defined using a grammar formalism. Attribute Multiset Grammars (AMG) are chosen because they allow defining hierarchies, as well as attribute rules and constraints. When used for recognition, detectors are employed to gather a set of detections. Parsing the set of detections by the AMG provides a global explanation. To find the best parse tree given a set of detections, a Bayesian network models the probability distribution over the space of possible parse trees. Heuristic and exhaustive search techniques are proposed to find the maximum a posteriori global explanation. The framework is tested for two activities: the activity in a bicycle rack, and around a building entrance. The first case study involves people locking bicycles onto a bicycle rack and picking them up later. The best global explanation for all detections gathered during the day resolves local ambiguities from occlusion or clutter. Intensive testing on 5 full days proved global analysis achieves higher recognition rates. The second case study tracks people and any objects they are carrying as they enter and exit a building entrance. A complete sequence of the person entering and exiting multiple times is recovered by the global explanation

Computer-aided exploration of architectural design spaces: a digital sketchbook

Het ontwerpproces van architecten vormt vaak geen lineair pad van ontwerpopgave tot eindresultaat, maar wordt veeleer gekenmerkt door exploratie of het doorzoeken van meerdere alternatieven in een (conceptuele) ontwerpruimte. Dit proces wordt in de praktijk vaak ondersteund door manueel schetsen, waarbij de ontwerpers schetsboek kan gelezen worden als een reeks exploraties. Dit soort interactie met de ontwerpruimte wordt in veel mindere mate ondersteund door hedendaagse computerondersteunde ontwerpsystemen. De metafoor van een digitaal schetsboek, waarbij menselijke exploratie wordt versterkt door de (reken)kracht van een computer, is het centrale onderzoeksthema van dit proefschrift. Hoewel het opzet van een ontwerpruimte op het eerste gezicht schatplichtig lijkt aan het onderzoeksveld van de artificiële intelligentie (AI), wordt het ontwerpen hier ruimer geïnterpreteerd dan het oplossen van problemen. Als onderzoeksmethodologie worden vormengrammatica’s ingezet, die enerzijds nauw aanleunen bij de AI en een formeel raamwerk bieden voor de exploratie van ontwerpruimtes, maar tegelijkertijd ook weerstand bieden tegen de AI en een vorm van visueel denken en ambiguïteit toelaten. De twee bijhorende onderzoeksvragen zijn hoe deze vormengrammatica’s digitaal kunnen worden gerepresenteerd, en op welke manier de ontwerper-computer interactie kan gebeuren. De resultaten van deze twee onderzoeksvragen vormen de basis van een nieuw hulpmiddel voor architecten: het digitaal schetsboek

On Repairing Structural Issues in Semi-Structured Documents

Ph.DDOCTOR OF PHILOSOPH

The role of terminology and local grammar in video annotation

The linguistic annotation' of video sequences is an intellectually challenging task involving the investigation of how images and words are linked .together, a task that is ultimately financially rewarding in that the eventual automatic retrieval of video (sequences) can be much less time consuming, subjective and expensive than when retrieved manually. Much effort has been focused on automatic or semi-automatic annotation. Computational linguistic methods of video annotation rely on collections of collateral text in the form of keywords and proper nouns. Keywords are often used in a particular order indicating an identifiable pattern which is often limited and can subsequently be used to annotate the portion of a video where such a pattern occurred. Once' the relevant keywords and patterns have been stored, they can then be used to annotate the remainder of the video, excluding all collateral text which does not match the keywords or patterns. A new method of video annotation is presented in this thesis. The method facilitates a) annotation extraction of specialist terms within a corpus of collateral text; b) annotation identification of frequently used linguistic patterns to use in repeating key events within the data-set. The use of the method has led to the development of a system that can automatically assign key words and key patterns to a number of frames that are found in the commentary text approximately contemporaneous to the selected number of frames. The system does not perform video analysis; it only analyses the collateral text. The method is based on corpus linguistics and is mainly frequency based - frequency of occurrence of a key word or key pattern is taken as the basis of its representation. No assumptions are made about the grammatical structure of the language used in the collateral text, neither is a lexica of key words refined. Our system has been designed to annotate videos of football matches in English a!ld Arabic, and also cricket videos in English. The system has also been designed to retrieve annotated clips. The system not only provides a simple search method for annotated clips retrieval, it also provides complex, more advanced search methods.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Advances in Computer Science and Engineering

The book Advances in Computer Science and Engineering constitutes the revised selection of 23 chapters written by scientists and researchers from all over the world. The chapters cover topics in the scientific fields of Applied Computing Techniques, Innovations in Mechanical Engineering, Electrical Engineering and Applications and Advances in Applied Modeling