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Image stitching algorithms construct a single composite high resolution image with a larger field of view using multiple low resolution images. Data wall systems combine the power of multiple graphics cards to provide large number of pixels. In this research work, we propose and implement scalable high resolution panorama composition on the data wall system using distributed rendering. We make use of a cross platform OpenGL library for real-time panorama composition. Our algorithm works for image sources with fixed relative positions. Initially, we employ an OpenCV image processing library for panorama calibration. Subsequently, these calibration results are utilized to generate a seamless panoramic image. We construct a high resolution 3×3 data wall system using commodity projectors. We achieve a seamless display with the help of geometric alignment of projector regions and edge blending in overlapping regions. Conventional display devices with their limited image resolution lose details provided by high resolution panorama because of data compression. We integrate panorama composition and the data wall system using distributed rendering. We distribute panorama composition to rendering workstations, which compute their respective screen space bounding regions and operate within it. It provides high resolution panorama with greater details on the data wall system.

Image stitching algorithms combine multiple low resolution images and provide a single high resolution composite image with a larger field of view available for video surveillance. In this research work, we put forward and realize real-time panorama composition for a video surveillance application using the power of a GPU. We utilize a cross platform OpenGL graphics library for real-time online image processing. We parallelize panorama composition using OpenGL objects such as texture object, vertex buffer object and framebuffer object for image warping as well as edge blending to create a seamless panoramic image. We divide our panorama composition algorithm into two stages for image sources with fixed relative positions with each other. Initially in an offline stage, we compute inverse lookup maps and feather weight masks using an OpenCV image processing library for each input image. Subsequently in an online stage, we utilize these inverse lookup maps to generate warped images, which are further edge blended with each other using feather weight masks with the help of OpenGL objects. Our panorama composition is more than 8.5 times faster than the CUDA optimized OpenCV realization. It produces a high resolution seamless panoramic image using nine input image streams each with 800×600 image resolution at about more than 75 frames per second using less than 90MB of GPU memory.

In this research work, we propose and realize a real-time stereoscopic vision system for neurosurgery training using a surgical stereoscopic microscope. We connect a pair of high resolution IP cameras to a surgical microscope through a dual port microscope beam splitter and a pair of microscope video adaptors. We make use of the specifically designed chessboard calibration pattern and an open source OpenCV library for system calibration. We perform local calibration to align individual IP camera views with each other, whereas global calibration is carried out to line up local calibrated camera views parallel with the user defined reference coordinate system. We calibrate our stereoscopic system using a single input image of the calibration pattern. We perform real-time stereo image remapping for the comfortable stereoscopic vision using a GPU. A media server is developed and introduced in between the IP camera pair and viewer applications to support multiple stereo image streams as well as to provide one more layer of protection to IP cameras. We make use of a NVIDIA 3D Vision Pro system and a 3D ready 120Hz monitor for active stereoscopic vision. We utilize HDMI-1.4 frame packing for passive stereoscopic vision on a standard 3D-TV. We measure network latency of our stereoscopic system with and without using the media server application, which is within acceptable limits. Finally, we compare NVIDIA 3D Vision Pro based active stereoscopic vision and passive stereoscopic vision using a 3D-TV with their pros and cons.

High resolution displays utilizing an array of commodity projectors are becoming popular approach(also called tiled displays) for visualizing high resolution content like scientific data-sets. These systems provide a relatively cheaper and flexible alternative to displays based on single high resolution monitor or projector. This approach inherently provides a method to create displays with resolution much higher than that possible by using a single high resolution display device. However, bezels in monitor based tiled displays obstruct the geometric continuity of the rendered content. In this paper, we describe the algorithms for geometric alignment of projection regions of an array of arbitrarily placed projectors and attenuation of projected intensities in the overlapping regions of multiple projectors using camera as a feedback device. Combination of these algorithms help us achieve a seamless high resolution display. We have observed improvements in fidelity of the rendered content by utilizing collinearity constraint in geometric alignment calculations. We also propose a novel technique based on cross-ratio invariant for utilizing full projection region of individual projectors which was limited by the size of features used for geometric alignment in the earlier approaches for planar displays. This also results in more imperceptible edge blending artifacts for same physical setup of projectors.

Robots are deployed to perform repeatable as well as hazardous tasks because of their inherent safety, reliability, consistency and accuracy. Recently robots are manipulated remotely using the binocular stereo vision. In this paper, we propose and implement a real-time stereoscopic viewer for telerobotics using open source software. We manipulate the KUKA KR-6 robot remotely using the Phantom haptic device. We assemble our stereo camera using a pair of IP cameras. We make use of the GStreamer multimedia framework for capturing and processing image streams coming from these IP cameras. We utilize the OpenCV library for camera calibration, stereo calibration and real-time stereo rectification. We extend predefined widgets from the Qt framework with our own widgets for the OpenGL based Quad buffering. We apply the software engineering design patterns for development of our in-house stereoscopic viewer. We also discuss the stereo vision using the DLP Link, the NVIDIA 3D Vision and the NVIDIA 3D Vision Pro with their pros and cons.

A visualization of large datasets requires ultra high resolution. Data wall systems provide large number of pixels by combining a power of multiple graphics cards. In this paper, we propose and realize an object oriented framework for the Message Passing Interface based parallel rendering. We introduce a GUI based viewer called the TiledRenderer, which is used for viewing pre-recorded high resolution animations as well as images on data walls. We identify a set of design patterns in a development of the TiledRenderer. We talk about benefits of using design patterns for extending our framework for adding the Real Time Streaming Protocol based IP camera support. We demonstrate that use of design patterns facilitates reusing the existing functionality and adding new functionality by providing new classes, rather than modifying the existing classes or functionality. We also discuss about a visualization of tsunami simulation data by using 6×6 data wall and the TiledRenderer.

Today we can have huge datasets resulting from computer simulations (FEA, CFD, physics, chemistry etc) and sensor measurements (medical, seismic and satellite). There is exponential growth in computational requirements in scientific research. Modern parallel computers and Grid are providing the required computational power for the simulation runs. The rich visualization is essential in interpreting the large, dynamic data generated from these simulation runs. The visualization process maps these datasets onto graphical representations and then generates the pixel representation. The large number of pixels shows the picture in greater details and interaction with it enables the greater insight on the part of user in understanding the data more quickly, picking out small anomalies that could turn out to be critical and make better decisions. However, the memory constraints in frame buffer, lack of the rendering power and the display resolution offered by even the most powerful graphics workstation makes the visualization of this magnitude difficult or impossible. This paper focuses on building an environment which render and drive over 47 millions of pixels, using the open source software framework. Our system’s display geometry is easy to configure and reconfigure, accommodates casually tiled displays and arbitrary display surfaces, and can be operational in a matter of minutes. In addition, the underlying distributed rendering architecture (chromium) is transparent to existing OpenGL applications, requiring no custom APIs or re-compilation of existing OpenGL executables. In short, we present a practical and flexible low-cost tiled display system that is simple to deploy and easy to operate. We also describe the software packages developed for such a system and its use to visualize data generated by computational simulations and applications requiring higher intrinsic display resolution and more display space.