Designing generalized data-driven distance measures for both ordered and unordered set data is the core focus of the proposed work. An ordered set is a set where time-linear property is maintained when distance between pair of temporal segments. One application in the ordered set is the human gesture analysis from RGBD data. Human gestures are fast becoming the natural form of human computer interaction. This serves as a motivation to modeling, analyzing, and recognition of gestures. The large number of gesture categories such as sign language, traffic signals, everyday actions and also subtle cultural variations in gesture classes makes gesture recognition a challenging problem. As part of generalization, an algorithm is proposed as part of an overlap speech detection application for unordered set. Any gesture recognition task involves comparing an incoming or a query gesture against a training set of gestures. Having one or few samples deters any class statistic learning approaches to classification, as the full range of variation is not covered. Due to the large variability in gesture classes, temporally segmenting individual gestures also becomes hard. A matching algorithm in such scenarios needs to be able to handle single sample classes and have the ability to label multiple gestures without temporal segmentation. Each gesture sequence is considered as a class and each class is a data point on an input space. A pair-wise distances pattern between to gesture frame sequences conditioned on a third (anchor) sequence is considered and is referred to as warp vectors. Such a process is defined as conditional distances. At the algorithmic core we have two dynamic time warping processes, one to compute the warp vectors with the anchor sequences and the other to compare these warp vectors. We show that having class dependent distance function can disambiguate classification process where the samples of classes are close to each other. Given a situation where the model base is large (number of classes is also large); the disadvantage of such a distance would be the computational cost. A distributed version combined with sub-sampling anchor gestures is proposed as speedup strategy. In order to label multiple connected gestures in query we use a simultaneous segmentation and recognition matching algorithm called level building algorithm. We use the dynamic programming implementation of the level building algorithm. The core of this algorithm depends on a distance function that compares two gesture sequences. We propose that, we replace this distance function, with the proposed distances. Hence, this version of level building is called as conditional level building (clb). We present results on a large dataset of 8000 RGBD sequences spanning over 200 gesture classes, extracted from the ChaLearn Gesture Challenge dataset. The result is that there is significant improvement over the underlying distance used to compute conditional distance when compared to conditional distance. As an application of unordered set and non-visual data, overlap speech segment detection algorithm is proposed. Speech recognition systems have a vast variety of application, but fail when there is overlap speech involved. This is especially true in a meeting-room setting. The ability to recognize speaker and localize him/her in the room is an important step towards a higher-level representation of the meeting dynamics. Similar to gesture recognition, a new distance function is defined and it serves as the core of the algorithm to distinguish between individual speech and overlap speech temporal segments. The overlap speech detection problem is framed as outlier detection problem. An incoming audio is broken into temporal segments based on Bayesian Information Criterion (BIC). Each of these segments is considered as node and conditional distance between the nodes are determined. The underlying distances for triples used in conditional distances is the symmetric KL distance. As each node is modeled as a Gaussian, the distance between the two segments or nodes is given by Monte-Carlo estimation of the KL distance. An MDS based global embedding is created based on the pairwise distance between the nodes and RANSAC is applied to compute the outliers. NIST meeting room data set is used to perform experiments on the overlap speech detection. An improvement of more than 20% is achieved with conditional distance based approach when compared to a KL distance based approach.

Dynamic programming has been widely used to solve various kinds of optimization problems.In this work, we show that two crucial problems in video-based sign language and gesture recognition systems can be attacked by dynamic programming with additional multiple observations. The first problem occurs at the higher (sentence) level. Movement epenthesis [1] (me), i.e., the necessary but meaningless movement between signs, can result in difficulties in modeling and scalability as the number of signs increases. The second problem occurs at the lower (feature) level. Ambiguity of hand detection and occlusion will propagate errors to the higher level. We construct a novel framework that can handle both of these problems based on a dynamic programming approach. The me has only be modeled explicitly in the past. Our proposed method tries to handle me in a dynamic programming framework where we model the me implicitly. We call this enhanced Level Building (eLB) algorithm. This formulation also allows the incorporation of statistical grammar models such as bigrams and trigrams. Another dynamic programming process that handles the problem of selecting among multiple hand candidates is also included in the feature level. This is different from most of the previous approaches, where a single observation is used. We also propose a grouping process that can generate multiple, overlapping hand candidates. We demonstrate our ideas on three continuous American Sign Language data sets and one hand gesture data set. The ASL data sets include one with a simple background, one with a simple background but with the signer wearing short sleeved clothes, and the last with a complex and changing background. The gesture data set contains color gloved gestures with a complex background. We achieve within 5% performance loss from the automatically chosen me score compared with the manually chosen me score. At the low level, we first over segment each frame to get a list of segments. Then we use a greedy method to group the segments based on different grouping cues. We also show that the performance loss is within 5% when we compare this method with manually selected feature vectors.

The key objective of this research is to develop a generic simulation modelling methodology that can be used to model stochastic continuous systems effectively. The generic methodology renders simulation models that exhibit the following characteristics: short development and maintenance times, user-friendliness, short simulation runtimes, compact size, robustness, accuracy and a single software application. The research was initiated by the shortcomings of a simulation modelling method that is detailed in a Magister dissertation. A system description of a continuous process plant (referred to as the Synthetic Fuel plant) is developed. The decision support role of simulation modelling is considered and the shortcomings of the original method are analysed. The key objective, importance and limitations of the research are also discussed. The characteristics of stochastic continuous systems are identified and a generic methodology that accommodates these characteristics is conceptualised and developed. It consists of the following eight methods and techniques: the variables technique, the iteration time interval evaluation method, the event-driven evaluation method, the Entity-represent-module method, the Fraction-comparison method, the iterative-loop technique, the time “bottleneck” identification technique and the production lost “bottleneck” identification technique. Five high-level simulation model building blocks are developed. The generic methodology is demonstrated and validated by the development and use of two simulation models. The five high-level building blocks are used to construct identical simulation models of the Synthetic Fuel plant in two different simulation software packages, namely: Arena and Simul8. An iteration time interval and minimum sufficient sample sizes are determined and the simulation models are verified, validated, enhanced and compared. The simulation models are used to evaluate two alternative scenarios. The results of the scenarios are compared and conclusions are presented. The factors that motivated the research, the process that was followed and the generic methodology are summarised. The original method and the generic methodology are compared and the strengths and weaknesses of the generic methodology are discussed. The contribution to knowledge is explained and future developments are proposed. The possible range of application and different usage perspectives are presented. To conclude, the lessons learnt and reinforced are considered. / Thesis (PhD (Industrial Engineering))--University of Pretoria, 2004. / Industrial and Systems Engineering / unrestricted

This is a thesis in Information design with focus on Spatial Design. This study examines how information can be shaped and placed in a multipurpose building to make it easier for the visitor to understand the place and find their way. The examined place is Kulturhuset in Hallstahammar, where the target audience is visitor who has no experience or very little experience of the place. The purpose of the thesis is to explore how information design in a spatial context can be designed to facilitate the understanding and simplify the orientability of a multi-story building, in a house with multipurpose.    Through literature studies, place analysis, survey with expert users and an analysis of similar projects, a design proposal has been produced that has been presented through rendered images. The results of the study show that a map of the building provides a clear overview of the premises and the activities Kulturhuset offers. Together with color coding and pictograms, visitors can easily see where their destination is and how to get there. / Detta är ett examensarbete inom informationsdesign med inriktning på rumslig gestaltning. Denna studien undersöker hur information kan utformas och placeras i en komplex yta för att underlätta för människor att förstå en plats och hitta rätt. Platsen som undersöks är Kulturhuset i Hallstahammar där målgruppen är nya besökare som inte har någon eller endast lite vetskap om platsen. Syftet med examensarbetet är att utforska hur informationsdesign i en rumslig kontext kan utformas för att underlätta förståelsen samt förenkla orienterbarheten i en flervåningsbyggnad, som inrymmer flera olika verksamheter.   Genom litteraturstudier, platsanalys, frågeformulär med expertanvändare samt en omvärldsanalys har ett gestaltningsförslag kunnat tagits fram som presenterats genom renderade bilder. Resultatet av studien påvisar att en karta över byggnaden ger en tydlig överblick över lokalerna samt verksamheterna som huserar i byggnaden. Tillsammans med färgkodning och piktogram kan besökare enkelt se vart deras slutmål för att sedan kunna ta sig dit.