Active binocular vision systems are powerful tools in machine vision. With a virtually unlimited field-of-view they have access to huge amounts of information, yet are able to confine their resources to specific regions of interest. Since they can dynamically interact with the environment, they are able to successfully address problems that are ill-posed to passive systems. A primary goal of an active binocular vision systems is to ascertain depth information. Since they employ two cameras and are able to sample a scene from two distinct vantage points, they are well suited for such a task. The depth recovery process is composed of two interrelated components: image registration and sampling. Image registration is the process of determining corresponding points between the stereo images. Once points in the images have been matched, 3D information can be recovered via triangulation. Image sampling determines how the image is discretized and represented. Image registration and sampling are highly interdependent. The choice of sampling scheme can profoundly impact the accuracy and complexity of the registrations process. In many situations, particular registration algorithms are simply incompatible with some sampling schemes. In this dissertation we meticulously address both registration and sampling in the context of stereopis for active binocular vision systems. Throughout the development of this work, contributions in each area are addressed with an eye toward their eventual integration into a cohesive registration procedure appropriate for active binocular vision systems. The actual synthesis is a daunting task that is beyond the scope of this single dissertation. The focus of this work is to assiduously analyze both registration and sampling, establishing a solid foundation for their future aggregation. One of the most successful approaches to image registration is phase-differencing. Phase-differencing algorithms provide a fast, powerful means for depth recovery. Unfortunately, phase-differencing techniques suffer from two significant impediments: phase nonlinearities and neglect of multispectral information. This dissertation uses the amenable properties of white noise images to analytically quantify the behavior of phase in these regions of phase nonlinearity. The improved understanding gained from this analysis enables us to create a new, more effective method for identifying these regions based on the second derivative of phase. We also suggest a novel approach that combines our method of nonlinear phase detection with strategies of both phase-differencing and local correlation. This hybrid approach retains the advantageous properties of phase-differencing while incorporating the multispectral aspects of local correlation. This task of registration is greatly simplified if the camera geometry is known and the search for corresponding points can be restricted to epipolar lines. Unfortunately, computation of epipolar lines for an active system requires calibration which can be both highly complex and inaccurate. While it is possible to register images without calibration information, such unconstrained algorithms are usually time consuming and prone to error. In this dissertation we propose compromise. Even without the instantaneous knowledge of the system geometry, we can restrict the region of correspondence by imposing limits on the possible range of configurations, and as a result, confine our search for matching points to what we refer to as epipolar spaces. For each point in one image, we define the corresponding epipolar space in the other image as the union of all associated epipolar lines over all possible system geometries. Epipolar spaces eliminate the need for calibration at the cost of an increased search region. Since the average size of a search space is directly related to the accuracy and efficiency of any registration algorithm, it is essential to mitigate the increase. The major contribution of this dissertation is the derivation of an optimal nonuniform sampling that minimizes the average area per epipolar space. / text

published_or_final_version / abstract / Computer Science / Master / Master of Philosophy

No description available.

The object of this thesis is to present two novel applications of Spatiotemporal Image Correlation Spectroscopy (STICS) to biological systems. STICS is a technique which uses the correlations in pixel intensity fluctuations of an image time series, captured under fluorescence microscopy, to measure the speed and direction of a flowing population of fluorescently labeled molecules. The method was first applied to measure the dynamics of transport vesicles inside growing pollen tubes of lily flowers. The measured vector maps allowed to confirm the presence of actin filaments along the periphery of the tubes, as well as the presence of a reverse-fountain pattern in the apical region. In a second set of experiments, STICS was used to measure the retrograde flow of filamentous actin in migrating chick DRG neuronal growth cones. These results serve as proof of principle that STICS can be used to probe the response of the growth cone cytoskeleton to external chemical cues.

Thesis (Ph. D.)--University of Hawaii at Manoa, 1995. / Includes bibliographical references (leaves 220-227). / Microfiche. / xiii, 227 leaves, bound ill. (some col.) 29 cm

No description available.

創意媒體研究中，圖像/視頻再藝術作為有表現力的用戶定制外觀的創作手段受到了很大關注。交互設計中，特別是在圖像空間只有單張圖像或視頻輸入的情況下，運用計算機輔助設計虛擬地再渲染關注物體的風格化外觀來實現紋理替換是很強大的。現行的紋理替換往往通過操作圖像空間中像素的間距來處理紋理扭曲，原始圖像中潛在的紋理扭曲總是被破壞，因為現行的方法要麼存在由於手動網格拉伸導致的不恰當扭曲，要麼就由於紋理合成而導致不可避免的紋理開裂。圖像/視頻拼貼畫是被發明用以支持在顯示畫布上並行展示多個物體和活動。隨著數字視頻俘獲裝置的快速發展，相關的議題就是快速檢閱和摘要大量的視覺媒體數據集來找出關注的資料。這會是一項繁瑣的任務來審查長且乏味的監控視頻並快速把握重要信息。以關鍵信息和縮短視頻形式為交流媒介，視頻摘要是增強視覺數據集瀏覽效率和簡易理解的手段。 / 本文首先將圖像/視頻再藝術聚焦在高效紋理替換和風格化上。我們展示了一種交互紋理替換方法，能夠在不知潛在幾何結構和光照環境的情況下保持相似的紋理扭曲。我們運用SIFT 棱角特徵來自然地發現潛在紋理扭曲，並應用梯度深度圖復原和皺褶重要性優化來完成扭曲過程。我們運用GPU-CUDA 的並行性，通過實時雙邊網格和特徵導向的扭曲優化來促成交互紋理替換。我們運用基於塊的實時高精度TV-L¹光流，通過基於關鍵幀的紋理傳遞來完成視頻紋理替換。我們進一步研究了基於GPU 的風格化方法，並運用梯度優化保持原始圖像的精細結構。我們提出了一種能夠自然建模原始圖像精細結構的圖像結構圖，並運用基於梯度的切線生成和切線導向的形態學來構建這個結構圖。我們在GPU-CUDA 上通過並行雙邊網格和結構保持促成最終風格化。實驗中，我們的方法實時連續地展現了高質量的圖像/視頻的抽象再藝術。 / 當前，視頻拼貼畫大多創作靜態的基於關鍵幀的拼貼圖片，該結果只包含動態視頻有限的信息，會很大程度影響視覺數據集的理解。爲了便於瀏覽，我們展示了一種在顯示畫布上有效並行摘要動態活動的動態視頻拼貼畫。我們提出應用活動長方體來重組織及提取事件，執行視頻防抖來生成穩定的活動長方體，實行時空域優化來優化活動長方體在三維拼貼空間的位置。我們通過在GPU 上的事件相似性和移動關係優化來完成高效的動態拼貼畫，允許多視頻輸入。擁有再序核函數CUDA 處理，我們的視頻拼貼畫爲便捷瀏覽長視頻激活了動態摘要，節省大量存儲傳輸空間。實驗和調查表明我們的動態拼貼畫快捷有效，能被廣泛應用于視頻摘要。將來，我們會擴展交互紋理替換來支持更複雜的具大運動和遮蔽場景的一般視頻，避免紋理跳動。我們會採用最新視頻技術靈感使視頻紋理替換更加穩定。我們未來關於視頻拼貼畫的工作包括審查監控業中動態拼貼畫應用，並研究含有大量相機運動和不同種視頻過度的移動相機和一般視頻。 / Image/video restyling as an expressive way for producing usercustomized appearances has received much attention in creative media researches. In interactive design, it would be powerful to re-render the stylized presentation of interested objects virtually using computer-aided design tools for retexturing, especially in the image space with a single image or video as input. The nowaday retexturing methods mostly process texture distortion by inter-pixel distance manipulation in image space, the underlying texture distortion is always destroyed due to limitations like improper distortion caused by human mesh stretching, or unavoidable texture splitting caused by texture synthesis. Image/ video collage techniques are invented to allow parallel presenting of multiple objects and events on the display canvas. With the rapid development of digital video capture devices, the related issues are to quickly review and brief such large amount of visual media datasets to find out interested video materials. It will be a tedious task to investigate long boring surveillance videos and grasp the essential information quickly. By applying key information and shortened video forms as vehicles for communication, video abstraction and summary are the means to enhance the browsing efficiency and easy understanding of visual media datasets. / In this thesis, we first focused our image/video restyling work on efficient retexturing and stylization. We present an interactive retexturing that preserves similar texture distortion without knowing the underlying geometry and lighting environment. We utilized SIFT corner features to naturally discover the underlying texture distortion. The gradient depth recovery and wrinkle stress optimization are applied to accomplish the distortion process. We facilitate the interactive retexturing via real-time bilateral grids and feature-guided distortion optimization using GPU-CUDA parallelism. Video retexturing is achieved through a keyframe-based texture transferring strategy using accurate TV-L¹ optical flow with patch motion tracking techniques in real-time. Further, we work on GPU-based abstract stylization that preserves the fine structure in the original images using gradient optimization. We propose an image structure map to naturally distill the fine structure of the original images. Gradientbased tangent generation and tangent-guided morphology are applied to build the structure map. We facilitate the final stylization via parallel bilateral grids and structure-aware stylizing in real-time on GPU-CUDA. In the experiments, our proposed methods consistently demonstrate high quality performance of image/video abstract restyling in real-time. / Currently, in video abstraction, video collages are mostly produced with static keyfame-based collage pictures, which contain limited information of dynamic videos and in uence understanding of visual media datasets greatly. We present dynamic video collage that effectively summarizes condensed dynamic activities in parallel on the canvas for easy browsing. We propose to utilize activity cuboids to reorganize and extract dynamic objects for further collaging, and video stabilization is performed to generate stabilized activity cuboids. Spatial-temporal optimization is carried out to optimize the positions of activity cuboids in the 3D collage space. We facilitate the efficient dynamic collage via event similarity and moving relationship optimization on GPU allowing multi-video inputs. Our video collage approach with kernel reordering CUDA processing enables dynamic summaries for easy browsing of long videos, while saving huge memory space for storing and transmitting them. The experiments and user study have shown the efficiency and usefulness of our dynamic video collage, which can be widely applied for video briefing and summary applications. In the future, we will further extend the interactive retexturing to more complicated general video applications with large motion and occluded scene avoiding textures icking. We will also work on new approaches to make video retexturing more stable by inspiration from latest video processing techniques. Our future work for video collage includes investigating applications of dynamic collage into the surveillance industry, and working on moving camera and general videos, which may contain large amount of camera motions and different types of video shot transitions. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Li, Ping. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 109-121). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgements --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Main Contributions --- p.5 / Chapter 1.3 --- Thesis Overview --- p.7 / Chapter 2 --- Efficient Image/video Retexturing --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- Related Work --- p.11 / Chapter 2.3 --- Image/video Retexturing on GPU --- p.16 / Chapter 2.3.1 --- Wrinkle Stress Optimization --- p.19 / Chapter 2.3.2 --- Efficient Video Retexturing --- p.24 / Chapter 2.3.3 --- Interactive Parallel Retexturing --- p.29 / Chapter 2.4 --- Results and Discussion --- p.35 / Chapter 2.5 --- Chapter Summary --- p.41 / Chapter 3 --- Structure-Aware Image Stylization --- p.43 / Chapter 3.1 --- Introduction --- p.43 / Chapter 3.2 --- Related Work --- p.46 / Chapter 3.3 --- Structure-Aware Stylization --- p.50 / Chapter 3.3.1 --- Approach Overview --- p.50 / Chapter 3.3.2 --- Gradient-Based Tangent Generation --- p.52 / Chapter 3.3.3 --- Tangent-Guided Image Morphology --- p.54 / Chapter 3.3.4 --- Structure-Aware Optimization --- p.56 / Chapter 3.3.5 --- GPU-Accelerated Stylization --- p.58 / Chapter 3.4 --- Results and Discussion --- p.61 / Chapter 3.5 --- Chapter Summary --- p.66 / Chapter 4 --- Dynamic Video Collage --- p.67 / Chapter 4.1 --- Introduction --- p.67 / Chapter 4.2 --- Related Work --- p.70 / Chapter 4.3 --- Dynamic Video Collage on GPU --- p.74 / Chapter 4.3.1 --- Activity Cuboid Generation --- p.75 / Chapter 4.3.2 --- Spatial-Temporal Optimization --- p.80 / Chapter 4.3.3 --- GPU-Accelerated Parallel Collage --- p.86 / Chapter 4.4 --- Results and Discussion --- p.90 / Chapter 4.5 --- Chapter Summary --- p.100 / Chapter 5 --- Conclusion --- p.101 / Chapter 5.1 --- Research Summary --- p.101 / Chapter 5.2 --- Future Work --- p.104 / Chapter A --- Publication List --- p.107 / Bibliography --- p.109

by Shen Hua. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 67-71). / Abstracts in English and Chinese. / Abstract --- p.i / 摘要 --- p.iii / Acknowledgments --- p.v / Table of Contents --- p.vii / List of Figures --- p.ix / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Object Detection --- p.2 / Chapter 1.2 --- Signboard Detection --- p.3 / Chapter Chapter 2 --- System Overview --- p.5 / Chapter 2.1 --- What is the problem? --- p.5 / Chapter 2.2 --- Review of previous work --- p.6 / Chapter 2.3 --- System Outline --- p.8 / Chapter Chapter 3 --- Preprocessing --- p.10 / Chapter 3.1 --- Edge Detection --- p.11 / Chapter 3.1.1 --- Gradient-Based Method --- p.11 / Chapter 3.1.2 --- Laplacian of Gaussian --- p.14 / Chapter 3.1.3 --- Canny edge detection --- p.15 / Chapter 3.2 --- Corner Detection --- p.18 / Chapter Chapter 4 --- Finding Candidate Lines --- p.22 / Chapter 4.1 --- Hough Transform --- p.22 / Chapter 4.1.1 --- What is Hough Transform --- p.22 / Chapter 4.1.2 --- Parameter Space --- p.22 / Chapter 4.1.3 --- Accumulator Array --- p.24 / Chapter 4.2 --- Gradient-based Hough Transform --- p.25 / Chapter 4.2.1 --- Direction of Gradient --- p.26 / Chapter 4.2.2 --- Accumulator Array --- p.28 / Chapter 4.2.3 --- Peaks in the accumulator array --- p.30 / Chapter 4.2.4 --- Performance of Gradient-based Hough Transform --- p.32 / Chapter Chapter 5 --- Signboards Locating --- p.35 / Chapter 5.1 --- Line Verification --- p.35 / Chapter 5.1.1 --- Line Segmentation --- p.35 / Chapter 5.1.2 --- Density Checking --- p.37 / Chapter 5.2 --- Finding Close Circuits --- p.40 / Chapter 5.3 --- Remove Redundant Segments --- p.47 / Chapter Chapter 6 --- Post processing --- p.54 / Chapter Chapter 7 --- Experiments and Conclusion --- p.59 / Chapter 7.1 --- Experimental Results --- p.59 / Chapter 7.2 --- Conclusion --- p.66 / Bibliography --- p.67

Functional magnetic resonance imaging (fMRI) is an extremely popular investigative and clinical imaging tool that allows safe and noninvasive study of the functional living brain. Fundamentally, fMRI measures a physiological signal as it changes over time. The manner in which this spatio-temporal signal is acquired can create technical challenges during image reconstruction that must be corrected for if any meaningful information is to be extracted from the data. Two particular challenges that are fundamentally intertwined with each other are temporal misalignment and spatial misalignment. Temporal misalignment is due to the nature of fMRI acquisition protocols themselves: a 3D volume is created by sampling and stacking multiple 2D slices. However, these slices are not acquired simultaneously or sequentially, and therefore will always be temporally misaligned with each other. Spatial misalignment arises when subject motion is present during the scan, resulting in individual volumes being spatially misaligned with each other. Spatial and temporal misalignment are not independent from each other, and their interaction can cause additional artifacts and reconstruction challenges if not addressed properly. The purpose of this thesis is to critically examine the problem of both spatial and temporal misalignment from a signal processing perspective, while considering the physical nature and origin of the signal itself, and develop optimal correction routines for spatial and temporal misalignment and their associated artifacts. One of the most immediate problems associated with temporal misalignment is that the order in which the slices are acquired must be known in order for correction to be possible. Surprisingly, this information is rarely provided with old or shared data, meaning that this critical preprocessing step must be skipped, significantly lowering the value of the data. We use the spatio-temporal properties of the fMRI signal to develop a robust and accurate algorithm to infer the slice acquisition order retrospectively from any fMRI scan. The ability to extract the interleave parameter from any data set allows us to perform slice timing correction even if this information had been lost, or was not provided with the scan. In the next section of this work, we develop a new optimal method of slice timing correction (Filter-Shift) based on the fundamental properties of sampling theory in digital signal processing. By examining the properties of the signal of interest (The blood oxygen level depended signal: BOLD signal), we are able to design and implement an effective FIR filter to simultaneously remove noise and reconstruct the signal of interest at any shifted offset, without the need for sub-optimal interpolation. In the final section, we investigate the effects of different motion types on the MR signal based on the Bloch equation, in order to develop a theoretical foundation from which we can create an optimal correction method. We devise a novel method to remove these artifacts: Discrete reconstruction of irregular fMRI trajectory (DRIFT). Our method calculates the exact displacement of the k-space samples due to motion at each dwell time and retrospectively corrects each slice of the fMRI volume using an inverse nonuniform Fourier transform. We conclude that a hybrid approach with both prospective and retrospective components are essentially required for optimal removal of motion artifacts from the fMRI data. The combined work of this thesis provides two theoretically sound and extremely effective correction routines, that both remove artifacts and restore the underlying sampled signal. Motion correction and slice timing correction are typically the first two preprocessing steps to be applied to any fMRI data, and thus provide the foundation for any further analysis. While many other preprocessing steps can be omitted or included depending on the analysis, motion correction and slice timing correction are unequivocally beneficial and necessary for accurate and reliable results. This work provides a theoretical and quantitative framework that describes the optimal removal of artifacts associated with motion and slice timing.

M. Tech. Electrical Engineering. / Proposes a power control algorithm for video transmission over WMNs. The proposed algorithm is implemented and simulation results compared with those of conventional IEEE 802.11b network.