This thesis introduces novel methods for estimating the poses of a reference plane from its reflections for specular surface recovery. Traditional methods for specular surface recovery usually introduce a second camera and an auxiliary calibration pattern to calibrate the poses of the reference plane with respect to the camera. The calibration procedures are comparatively tedious. Auto-estimating the poses of the reference plane is therefore an appealing problem. In the first part of this thesis, two novel and practical methods are proposed to recover the poses of a moving reference plane from its reflections produced on the specular surface given its initial position. As for the first approach, the reference plane is constrained to undergo an unknown pure translation. By observing the reflections of the moving reference plane produced on the specular surface, a closed form solution is derived for recovering the unknown translation. Degenerate cases in which the proposed method fails are studied. As for the second approach, the constraint on the motion of the reference plane is removed, and the reference plane can move freely. Again, a closed form solution is derived for the unknown motion defined by a rotation matrix and a translation vector, and the degenerate cases are also presented. The thesis finally considers the problem for auto-calibrating the reference plane against the camera for specular surface recovery without prior knowledge of the reference plane’s initial position. By only observing its reflections produced on the specular surface, the poses of the reference planes can be recovered in two steps. First, by applying a collinearity constraint to the specular correspondences, a simple closed form solution is derived for recovering the poses of the reference plane relative to its initial pose. Second, by applying a ray incidence constraint to the incident rays formed by the specular correspondences and the visual rays cast from the image, a closed form solution is derived for recovering the poses of the reference plane relative to the camera. The shape of the specular surface then follows. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

RNA-seq sequencing has revolutionized the landscape of whole transcriptome sequencing and analysis. With its capacity of sequencing in a high-throughput and low-cost way, it produced ever increasingly amount of RNA-seq reads that are mines of treasure in biological and therapeutic studies. However, due to the complex nature and relatively un-developed knowledge base of transcription process, many challenges exist in the modeling and investigation of RNA-seq read data. It is of high importance to develop efficient computational tools to satisfy these needs. The first part of this thesis concentrates on algorithms for both upstream and downstream analysis of RNA-seq data. For the upstream, we aim to tackle down the problems of RNA-seq reads alignment where the segmental alignment causes the major difficulty. By employing a strategy of rigid extensive tries on read segmentations indices, we implemented an accurate algorithm for returning two-segmental alignments based on bi-directional BWT. For the downstream analysis, we study two types of gene fusion events which play a critical role in the formation of cancers. Unlike previous down-scoping-search methods, we applied a search-validate approach to design the framework. By introducing key techniques such as masking, two-segmental alignment and retention of multiple maps, we developed an efficient and robust tool for detecting gene fusions with high accuracy that proved by extensive simulation and real data tests. Optical mapping is a cutting edge technique for the study of genomic structural variations which address the defect and limitation of paired-end sequencing. It was designed with great improvement in accuracy, resolution and throughput than current techniques. Also, it produces much longer molecules which enables us to explore genomic regions rich in repetitive sequences. Optical mapping has the potential to enable us to draw a complete picture of the genome structure polymorphism and it is important for us to design tools for analysis of the data. The second part of the thesis is dedicated to the algorithms for both upstream and downstream analysis of optical map data. For the upstream, we formulated a robust scoring function, which combines the effectiveness of heuristic functions and the accuracy of statistical functions. Based on it, we implemented the high performance OMDP algorithm. For the downstream, we developed BP-OMDP which makes use of both split-mapping and disparity of coverage depth to call inversions in NA12878 human genome sample. / published_or_final_version / Computer science / Doctoral / Doctor of Philosophy

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published_or_final_version / Computer Science / Master / Master of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / Computer Science / Master / Master of Philosophy

published_or_final_version / Computer Science / Master / Master of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy