3D-TV Production from Conventional Cameras for Sports Broadcast

3DTV production of live sports events presents a challenging problem involving conflicting requirements of main- taining broadcast stereo picture quality with practical problems in developing robust systems for cost effective deployment. In this paper we propose an alternative approach to stereo production in sports events using the conventional monocular broadcast cameras for 3D reconstruction of the event and subsequent stereo rendering. This approach has the potential advantage over stereo camera rigs of recovering full scene depth, allowing inter-ocular distance and convergence to be adapted according to the requirements of the target display and enabling stereo coverage from both existing and ‘virtual’ camera positions without additional cameras. A prototype system is presented with results of sports TV production trials for rendering of stereo and free-viewpoint video sequences of soccer and rugby

Conceptual design study for a teleoperator visual system, phase 2

An analysis of the concept for the hybrid stereo-monoscopic television visual system is reported. The visual concept is described along with the following subsystems: illumination, deployment/articulation, telecommunications, visual displays, and the controls and display station

Portal-s: High-resolution real-time 3D video telepresence

The goal of telepresence is to allow a person to feel as if they are present in a location other than their true location; a common application of telepresence is video conferencing in which live video of a user is transmitted to a remote location for viewing. In conventional two-dimensional (2D) video conferencing, loss of correct eye gaze commonly occurs, due to a disparity between the capture and display optical axes. Newer systems are being developed which allow for three-dimensional (3D) video conferencing, circumventing issues with this disparity, but new challenges are arising in the capture, delivery, and redisplay of 3D contents across existing infrastructure. To address these challenges, a novel system is proposed which allows for 3D video conferencing across existing networks while delivering full resolution 3D video and establishing correct eye gaze. During the development of Portal-s, many innovations to the field of 3D scanning and its applications were made; specifically, this dissertation research has achieved the following innovations: a technique to realize 3D video processing entirely on a graphics processing unit (GPU), methods to compress 3D videos on a GPU, and combination of the aforementioned innovations with a special holographic display hardware system to enable the novel 3D telepresence system entitled Portal-s. The first challenge this dissertation addresses is the cost of real-time 3D scanning technology, both from a monetary and computing power perspective. New advancements in 3D scanning and computation technology are continuing to increase, simplifying the acquisition and display of 3D data. These advancements are allowing users new methods of interaction and analysis of the 3D world around them. Although the acquisition of static 3D geometry is becoming easy, the same cannot be said of dynamic geometry, since all aspects of the 3D processing pipeline, capture, processing, and display, must be realized in real-time simultaneously. Conventional approaches to solve these problems utilize workstation computers with powerful central processing units (CPUs) and GPUs to accomplish the large amounts of processing power required for a single 3D frame. A challenge arises when trying to realize real-time 3D scanning on commodity hardware such as a laptop computer. To address the cost of a real-time 3D scanning system, an entirely parallel 3D data processing pipeline that makes use of a multi-frequency phase-shifting technique is presented. This novel processing pipeline can achieve simultaneous 3D data capturing, processing, and display at 30 frames per second (fps) on a laptop computer. By implementing the pipeline within the OpenGL Shading Language (GLSL), nearly any modern computer with a dedicated graphics device can run the pipeline. Making use of multiple threads sharing GPU resources and direct memory access transfers, high frame rates on low compute power devices can be achieved. Although these advancements allow for low compute power devices such as a laptop to achieve real-time 3D scanning, this technique is not without challenges. The main challenge being selecting frequencies that allow for high quality phase, yet do not include phase jumps in equivalent frequencies. To address this issue, a new modified multi-frequency phase shifting technique was developed that allows phase jumps to be introduced in equivalent frequencies yet unwrapped in parallel, increasing phase quality and reducing reconstruction error. Utilizing these techniques, a real-time 3D scanner was developed that captures 3D geometry at 30 fps with a root mean square error (RMSE) of 0:00081 mm for a measurement area of 100 mm X 75 mm at a resolution of 800 X 600 on a laptop computer. With the above mentioned pipeline the CPU is nearly idle, freeing it to perform additional tasks such as image processing and analysis. The second challenge this dissertation addresses is associated with delivering huge amounts of 3D video data in real-time across existing network infrastructure. As the speed of 3D scanning continues to increase, and real-time scanning is achieved on low compute power devices, a way of compressing the massive amounts of 3D data being generated is needed. At a scan resolution of 800 X 600, streaming a 3D point cloud at 30 frames per second (FPS) would require a throughput of over 1.3 Gbps. This amount of throughput is large for a PCIe bus, and too much for most commodity network cards. Conventional approaches involve serializing the data into a compressible state such as a polygon file format (PLY) or Wavefront object (OBJ) file. While this technique works well for structured 3D geometry, such as that created with computer aided drafting (CAD) or 3D modeling software, this does not hold true for 3D scanned data as it is inherently unstructured. A challenge arises when trying to compress this unstructured 3D information in such a way that it can be easily utilized with existing infrastructure. To address the need for real-time 3D video compression, new techniques entitled Holoimage and Holovideo are presented, which have the ability to compress, respectively, 3D geometry and 3D video into 2D counterparts and apply both lossless and lossy encoding. Similar to the aforementioned 3D scanning pipeline, these techniques make use of a completely parallel pipeline for encoding and decoding; this affords high speed processing on the GPU, as well as compression before streaming the data over the PCIe bus. Once in the compressed 2D state, the information can be streamed and saved until the 3D information is needed, at which point 3D geometry can be reconstructed while maintaining a low amount of reconstruction error. Further enhancements of the technique have allowed additional information, such as texture information, to be encoded by reducing the bit rate of the data through image dithering. This allows both the 3D video and associated 2D texture information to be interlaced and compressed into 2D video, synchronizing the streams automatically. The third challenge this dissertation addresses is achieving correct eye gaze in video conferencing. In 2D video conferencing, loss of correct eye gaze commonly occurs, due to a disparity between the capture and display optical axes. Conventional approaches to mitigate this issue involve either reducing the angle of disparity between the axes by increasing the distance of the user to the system, or merging the axes through the use of beam splitters. Newer approaches to this issue make use of 3D capture and display technology, as the angle of disparity can be corrected through transforms of the 3D data. Challenges arise when trying to create such novel systems, as all aspects of the pipeline, capture, transmission, and redisplay must be simultaneously achieved in real-time with the massive amounts of 3D data. Finally, the Portal-s system is presented, which is an integration of all the aforementioned technologies into a holistic software and hardware system that enables real-time 3D video conferencing with correct mutual eye gaze. To overcome the loss of eye contact in conventional video conferencing, Portal-s makes use of dual structured-light scanners that capture through the same optical axis as the display. The real-time 3D video frames generated on the GPU are then compressed using the Holovideo technique. This allows the 3D video to be streamed across a conventional network or the Internet, and redisplayed at a remote node for another user on the Holographic display glass. Utilizing two connected Portal-s nodes, users of the systems can engage in 3D video conferencing with natural eye gaze established. In conclusion, this dissertation research substantially advances the field of real-time 3D scanning and its applications. Contributions of this research span into both academic and industrial practices, where the use of this information has allowed users new methods of interaction and analysis of the 3D world around them

Camera positioning for 3D panoramic image rendering

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.Virtual camera realisation and the proposition of trapezoidal camera architecture are the two broad contributions of this thesis. Firstly, multiple camera and their arrangement constitute a critical component which affect the integrity of visual content acquisition for multi-view video. Currently, linear, convergence, and divergence arrays are the prominent camera topologies adopted. However, the large number of cameras required and their synchronisation are two of prominent challenges usually encountered. The use of virtual cameras can significantly reduce the number of physical cameras used with respect to any of the known camera structures, hence adequately reducing some of the other implementation issues. This thesis explores to use image-based rendering with and without geometry in the implementations leading to the realisation of virtual cameras. The virtual camera implementation was carried out from the perspective of depth map (geometry) and use of multiple image samples (no geometry). Prior to the virtual camera realisation, the generation of depth map was investigated using region match measures widely known for solving image point correspondence problem. The constructed depth maps have been compare with the ones generated using the dynamic programming approach. In both the geometry and no geometry approaches, the virtual cameras lead to the rendering of views from a textured depth map, construction of 3D panoramic image of a scene by stitching multiple image samples and performing superposition on them, and computation of virtual scene from a stereo pair of panoramic images. The quality of these rendered images were assessed through the use of either objective or subjective analysis in Imatest software. Further more, metric reconstruction of a scene was performed by re-projection of the pixel points from multiple image samples with a single centre of projection. This was done using sparse bundle adjustment algorithm. The statistical summary obtained after the application of this algorithm provides a gauge for the efficiency of the optimisation step. The optimised data was then visualised in Meshlab software environment, hence providing the reconstructed scene. Secondly, with any of the well-established camera arrangements, all cameras are usually constrained to the same horizontal plane. Therefore, occlusion becomes an extremely challenging problem, and a robust camera set-up is required in order to resolve strongly the hidden part of any scene objects. To adequately meet the visibility condition for scene objects and given that occlusion of the same scene objects can occur, a multi-plane camera structure is highly desirable. Therefore, this thesis also explore trapezoidal camera structure for image acquisition. The approach here is to assess the feasibility and potential of several physical cameras of the same model being sparsely arranged on the edge of an efficient trapezoid graph. This is implemented both Matlab and Maya. The quality of the depth maps rendered in Matlab are better in Quality

Vision Sensors and Edge Detection

Vision Sensors and Edge Detection book reflects a selection of recent developments within the area of vision sensors and edge detection. There are two sections in this book. The first section presents vision sensors with applications to panoramic vision sensors, wireless vision sensors, and automated vision sensor inspection, and the second one shows image processing techniques, such as, image measurements, image transformations, filtering, and parallel computing