Automated Detection and Counting of Pedestrians on an Urban Roadside

This thesis implements an automated system that counts pedestrians with 85% accuracy. Two approaches have been considered and evaluated in terms of count accuracy, cost and ease of deployment. The first approach employs the Autoscope Solo Terra, a traffic camera which is widely used to monitor vehicular traffic. The Solo Terra supports an image processing-based detector that counts the number of objects crossing user-defined areas in the captured image. The count is updated based on the amount of movement across the selected regions. Therefore, a second approach has been considered that uses a histogram of oriented gradients (HoG), an advanced vision based algorithm proposed by Dalal et al. which distinguishes a pedestrian from a non-pedestrian based on an omega shape formed by the head and shoulders of a human being. The implemented detection software processes video frames that are streamed from a low-cost digital camera. The frames are divided into sub-regions which are scanned for an omega shape whenever movement is detected in those regions. It has been found that the HoG-based approach degrades in performance due to occlusion under dense pedestrian traffic conditions whereas the Solo Terra approach appears to be more robust. Undercounts and overcounts were encountered using the Solo Terra approach. To combat the disadvantages of both the approaches, they were integrated to form a single system where count is incremented predominantly using the Solo Terra. The HoG-based approach corrects the obtained count under certain conditions. A preliminary prototype of the integrated system has been verified

Remote access computed tomography colonography

This thesis presents a novel framework for remote access Computed Tomography Colonography (CTC). The proposed framework consists of several integrated components: medical image data delivery, 2D image processing, 3D visualisation, and feedback provision. Medical image data sets are notoriously large and preserving the integrity of the patient data is essential. This makes real-time delivery and visualisation a key challenge. The main contribution of this work is the development of an efficient, lossless compression scheme to minimise the size of the data to be transmitted, thereby alleviating transmission time delays. The scheme utilises prior knowledge of anatomical information to divide the data into specific regions. An optimised compression method for each anatomical region is then applied. An evaluation of this compression technique shows that the proposed ‘divide and conquer’ approach significantly improves upon the level of compression achieved using more traditional global compression schemes. Another contribution of this work resides in the development of an improved volume rendering technique that provides real-time 3D visualisations of regions within CTC data sets. Unlike previous hardware acceleration methods which rely on dedicated devices, this approach employs a series of software acceleration techniques based on the characteristic properties of CTC data. A quantitative and qualitative evaluation indicates that the proposed method achieves real-time performance on a low-cost PC platform without sacrificing any image quality. Fast data delivery and real-time volume rendering represent the key features that are required for remote access CTC. These features are ultimately combined with other relevant CTC functionality to create a comprehensive, high-performance CTC framework, which makes remote access CTC feasible, even in the case of standard Web clients with low-speed data connections

Efficient deformable filter banks

This article describes efficient schemes for the computation of a large number of differently scaled/oriented filtered versions of an image. We generalize the well-known steerable/scalable (“deformable”) filter bank structure by imposing X-Y separability on the basis filters. The resulting systems, designed by an iterative projections technique, achieve substantial reduction of the computational cost. To reduce the memory requirement, we adopt a multirate implementation. Due to the inner sampling rate alteration, the resulting structure is not shift invariant. We introduce a design criterion for multirate deformable structures that jointly controls the approximation error and the shift variance

Efficient data structures for piecewise-smooth video processing

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 95-102).A number of useful image and video processing techniques, ranging from low level operations such as denoising and detail enhancement to higher level methods such as object manipulation and special effects, rely on piecewise-smooth functions computed from the input data. In this thesis, we present two computationally efficient data structures for representing piecewise-smooth visual information and demonstrate how they can dramatically simplify and accelerate a variety of video processing algorithms. We start by introducing the bilateral grid, an image representation that explicitly accounts for intensity edges. By interpreting brightness values as Euclidean coordinates, the bilateral grid enables simple expressions for edge-aware filters. Smooth functions defined on the bilateral grid are piecewise-smooth in image space. Within this framework, we derive efficient reinterpretations of a number of edge-aware filters commonly used in computational photography as operations on the bilateral grid, including the bilateral filter, edgeaware scattered data interpolation, and local histogram equalization. We also show how these techniques can be easily parallelized onto modern graphics hardware for real-time processing of high definition video. The second data structure we introduce is the video mesh, designed as a flexible central data structure for general-purpose video editing. It represents objects in a video sequence as 2.5D "paper cutouts" and allows interactive editing of moving objects and modeling of depth, which enables 3D effects and post-exposure camera control. In our representation, we assume that motion and depth are piecewise-smooth, and encode them sparsely as a set of points tracked over time. The video mesh is a triangulation over this point set and per-pixel information is obtained by interpolation. To handle occlusions and detailed object boundaries, we rely on the user to rotoscope the scene at a sparse set of frames using spline curves. We introduce an algorithm to robustly and automatically cut the mesh into local layers with proper occlusion topology, and propagate the splines to the remaining frames. Object boundaries are refined with per-pixel alpha mattes. At its core, the video mesh is a collection of texture-mapped triangles, which we can edit and render interactively using graphics hardware. We demonstrate the effectiveness of our representation with special effects such as 3D viewpoint changes, object insertion, depthof- field manipulation, and 2D to 3D video conversion.by Jiawen Chen.Ph.D

Incremental volume rendering using hierarchical compression

Includes bibliographical references.The research has been based on the thesis that efficient volume rendering of datasets, contained on the Internet, can be achieved on average personal workstations. We present a new algorithm here for efficient incremental rendering of volumetric datasets. The primary goal of this algorithm is to give average workstations the ability to efficiently render volume data received over relatively low bandwidth network links in such a way that rapid user feedback is maintained. Common limitations of workstation rendering of volume data include: large memory overheads, the requirement of expensive rendering hardware, and high speed processing ability. The rendering algorithm presented here overcomes these problems by making use of the efficient Shear-Warp Factorisation method which does not require specialised graphics hardware. However the original Shear-Warp algorithm suffers from a high memory overhead and does not provide for incremental rendering which is required should rapid user feedback be maintained. Our algorithm represents the volumetric data using a hierarchical data structure which provides for the incremental classification and rendering of volume data. This exploits the multiscale nature of the octree data structure. The algorithm reduces the memory footprint of the original Shear-Warp Factorisation algorithm by a factor of more than two, while maintaining good rendering performance. These factors make our octree algorithm more suitable for implementation on average desktop workstations for the purposes of interactive exploration of volume models over a network. This dissertation covers the theory and practice of developing the octree based Shear-Warp algorithms, and then presents the results of extensive empirical testing. The results, using typical volume datasets, demonstrate the ability of the algorithm to achieve high rendering rates for both incremental rendering and standard rendering while reducing the runtime memory requirements

Hardware accelerated computer graphics algorithms

The advent of shaders in the latest generations of graphics hardware, which has made consumer level graphics hardware partially programmable, makes now an ideal time to investigate new graphical techniques and algorithms as well as attempting to improve upon existing ones. This work looks at areas of current interest within the graphics community such as Texture Filtering, Bump Mapping and Depth of Field simulation. These are all areas which have enjoyed much interest over the history of computer graphics but which provide a great deal of scope for further investigation in the light of recent hardware advances. A new hardware implementation of a texture filtering technique, aimed at consumer level hardware, is presented. This novel technique utilises Fourier space image filtering to reduce aliasing. Investigation shows that the technique provides reduced levels of aliasing along with comparable levels of detail to currently popular techniques. This adds to the community's knowledge by expanding the range of techniques available, as well as increasing the number of techniques which offer the potential for easy integration with current consumer level graphics hardware along with real-time performance. Bump mapping is a long-standing and well understood technique. Variations and extensions of it have been popular in real-time 3D computer graphics for many years. A new hardware implementation of a technique termed Super Bump Mapping (SBM) is introduced. Expanding on the work of Cant and Langensiepen [1], the SBM technique adopts the novel approach of using normal maps which supply multiple vectors per texel. This allows the retention of much more detail and overcomes some of the aliasing deficiencies of standard bump mapping caused by the standard single vector approach and the non-linearity of the bump mapping process. A novel depth of field algorithm is proposed, which is an extension of the authors previous work [2][3][4]. The technique is aimed at consumer level hardware and attempts to raise the bar for realism by providing support for the 'see-through' effect. This effect is a vital factor in the realistic appearance of simulated depth of field and has been overlooked in real time computer graphics due to the complexities of an accurate calculation. The implementation of this new algorithm on current consumer level hardware is investigated and it is concluded that while current hardware is not yet capable enough, future iterations will provide the necessary functional and performance increases

Breastfeeding, brain activation to own infant cry, and maternal sensitivity

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87031/1/j.1469-7610.2011.02406.x.pd