This thesis analyzes the problem of acquiring stereoscopic images in all gazing directions around a reference viewpoint in space with the purpose of creating stereoscopic panoramas of non-static scenes. The generation of immersive stereoscopic imagery suitable to stimulate human stereopsis requires images from two distinct viewpoints with horizontal parallax in all gazing directions, or to be able to simulate this situation in the generated imagery. The available techniques to produce omnistereoscopic imagery for human viewing are not suitable to capture dynamic scenes stereoscopically. This is a not trivial problem when considering acquiring the entire scene at once while avoiding self-occlusion between multiple cameras. In this thesis, the term omnidirectional refers to all possible gazing directions in azimuth and a limited set of directions in elevation. The acquisition of dynamic scenes restricts the problem to those techniques suitable for collecting in one simultaneous exposure all the necessary visual information to recreate stereoscopic imagery in arbitrary gazing directions. The analysis of the problem starts by defining an omnistereoscopic viewing model for the physical magnitude to be measured by a panoramic image sensor intended to produce stereoscopic imagery for human viewing. Based on this model, a novel acquisition model is proposed, which is suitable to describe the omnistereoscopic techniques based on horizontal stereo. From this acquisition model, an acquisition method based on multiple cameras combined with the rendering by mosaicking of partially overlapped stereoscopic images is identified as a good candidate to produce omnistereoscopic imagery of dynamic scenes. Experimental acquisition and rendering tests were performed for different multiple-camera configurations. Furthermore, a mosaicking criterion between partially overlapped stereoscopic images based on the continuity of the perceived depth and the prediction of the location and magnitude of unwanted vertical disparities in the final stereoscopic panorama are two main contributions of this thesis. In addition, two novel omnistereoscopic acquisition and rendering techniques were introduced. The main contributions to this field are to propose a general model for the acquisition of omnistereoscopic imagery, to devise novel methods to produce omnistereoscopic imagery, and more importantly, to contribute to the awareness of the problem of acquiring dynamic scenes within the scope of omnistereoscopic research.

This thesis deals with issues automatic composing panoramic photos from individual photos. Gradually examines the various steps of algorithms and methods used in them, which are used in creating panoramas. It also focuses on the design of the own system based on methods discussed to construct panoramas. This system is implemented using OpenCV library and it is created also a graphical interface using a Qt library. Finally, are in this thesis evaluated outcomes of this designed and implemented system on available datasets.

Panoramas or stitched images are used in topographical mapping, panoramic 3D reconstruction, deep space exploration image processing, medical image processing, multimedia broadcasting, system automation, photography and other numerous fields. Generating real-time panoramic images in small embedded computer is of particular importance being lighter, smaller and mobile imaging system. Moreover, this type of lightweight panoramic imaging system is used for different types of industrial or home inspection. A real-time handheld panorama imaging system is developed using embedded real-time Linux as software module and Gumstix Overo and PandaBoard ES as hardware module. The proposed algorithm takes 62.6602 milliseconds to generate a panorama frame from three images using a homography matrix. Hence, the proposed algorithm is capable of generating panorama video with 15.95909365 frames per second. However, the algorithm is capable to be much speedier with more optimal homography matrix. During the development, Ångström Linux and Ubuntu Linux are used as the operating system with Gumstix Overo and PandaBoard ES respectively. The real-time kernel patch is used to configure the non-real-time Linux distribution for real-time operation. The serial communication software tools C-Kermit, Minicom are used for terminal emulation between development computer and small embedded computer. The software framework of the system consist UVC driver, V4L/V4L2 API, OpenCV API, FFMPEG API, GStreamer, x264, Cmake, Make software packages. The software framework of the system also consist stitching algorithm that has been adopted from available stitching methods with necessary modification. Our proposed stitching process automatically finds out motion model of the Spherical camera system and saves the matrix in a look file. The extracted homography matrix is then read from look file and used to generate real-time panorama image. The developed system generates real-time 180° view panorama image from a spherical camera system. Beside, a test environment is also developed to experiment calibration and real-time stitching with different image parameters. It is able to take images with different resolutions as input and produce high quality real-time panorama image. The QT framework is used to develop a multifunctional standalone software that has functions for displaying real-time process algorithm performance in real-time through data visualization, camera system calibration and other stitching options. The software runs both in Linux and Windows. Moreover, the system has been also realized as a prototype to develop a chimney inspection system for a local company. / Main Uddin-Al-Hasan, E-mail: main.hasan@gmail.com