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

3D video coding and transmission

The capture, transmission, and display of 3D content has gained a lot of attention in the last few years. 3D multimedia content is no longer con fined to cinema theatres but is being transmitted using stereoscopic video over satellite, shared on Blu-RayTMdisks, or sent over Internet technologies. Stereoscopic displays are needed at the receiving end and the viewer needs to wear special glasses to present the two versions of the video to the human vision system that then generates the 3D illusion. To be more e ffective and improve the immersive experience, more views are acquired from a larger number of cameras and presented on di fferent displays, such as autostereoscopic and light field displays. These multiple views, combined with depth data, also allow enhanced user experiences and new forms of interaction with the 3D content from virtual viewpoints. This type of audiovisual information is represented by a huge amount of data that needs to be compressed and transmitted over bandwidth-limited channels. Part of the COST Action IC1105 \3D Content Creation, Coding and Transmission over Future Media Networks" (3DConTourNet) focuses on this research challenge.peer-reviewe

Holographic and 3D teleconferencing and visualization: implications for terabit networked applications

Abstract not available

A framework for realistic 3D tele-immersion

Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite differ- ent from the experience of meeting face to face. We are abruptly aware that we are online and that the people we are engaging with are not in close proximity. Analogous to how talking on the telephone does not replicate the experi- ence of talking in person. Several causes for these differences have been identified and we propose inspiring and innova- tive solutions to these hurdles in attempt to provide a more realistic, believable and engaging online conversational expe- rience. We present the distributed and scalable framework REVERIE that provides a balanced mix of these solutions. Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic ex- periences to a multitude of users that for them will feel much more similar to having face to face meetings than the expe- rience offered by conventional teleconferencing systems

A fast and robust hand-driven 3D mouse

The development of new interaction paradigms requires a natural interaction. This means that people should be able to interact with technology with the same models used to interact with everyday real life, that is through gestures, expressions, voice. Following this idea, in this paper we propose a non intrusive vision based tracking system able to capture hand motion and simple hand gestures. The proposed device allows to use the hand as a "natural" 3D mouse, where the forefinger tip or the palm centre are used to identify a 3D marker and the hand gesture can be used to simulate the mouse buttons. The approach is based on a monoscopic tracking algorithm which is computationally fast and robust against noise and cluttered backgrounds. Two image streams are processed in parallel exploiting multi-core architectures, and their results are combined to obtain a constrained stereoscopic problem. The system has been implemented and thoroughly tested in an experimental environment where the 3D hand mouse has been used to interact with objects in a virtual reality application. We also provide results about the performances of the tracker, which demonstrate precision and robustness of the proposed syste

Total Variation Regularized Tensor RPCA for Background Subtraction from Compressive Measurements

Background subtraction has been a fundamental and widely studied task in video analysis, with a wide range of applications in video surveillance, teleconferencing and 3D modeling. Recently, motivated by compressive imaging, background subtraction from compressive measurements (BSCM) is becoming an active research task in video surveillance. In this paper, we propose a novel tensor-based robust PCA (TenRPCA) approach for BSCM by decomposing video frames into backgrounds with spatial-temporal correlations and foregrounds with spatio-temporal continuity in a tensor framework. In this approach, we use 3D total variation (TV) to enhance the spatio-temporal continuity of foregrounds, and Tucker decomposition to model the spatio-temporal correlations of video background. Based on this idea, we design a basic tensor RPCA model over the video frames, dubbed as the holistic TenRPCA model (H-TenRPCA). To characterize the correlations among the groups of similar 3D patches of video background, we further design a patch-group-based tensor RPCA model (PG-TenRPCA) by joint tensor Tucker decompositions of 3D patch groups for modeling the video background. Efficient algorithms using alternating direction method of multipliers (ADMM) are developed to solve the proposed models. Extensive experiments on simulated and real-world videos demonstrate the superiority of the proposed approaches over the existing state-of-the-art approaches.Comment: To appear in IEEE TI

Scalable Dense Monocular Surface Reconstruction

This paper reports on a novel template-free monocular non-rigid surface reconstruction approach. Existing techniques using motion and deformation cues rely on multiple prior assumptions, are often computationally expensive and do not perform equally well across the variety of data sets. In contrast, the proposed Scalable Monocular Surface Reconstruction (SMSR) combines strengths of several algorithms, i.e., it is scalable with the number of points, can handle sparse and dense settings as well as different types of motions and deformations. We estimate camera pose by singular value thresholding and proximal gradient. Our formulation adopts alternating direction method of multipliers which converges in linear time for large point track matrices. In the proposed SMSR, trajectory space constraints are integrated by smoothing of the measurement matrix. In the extensive experiments, SMSR is demonstrated to consistently achieve state-of-the-art accuracy on a wide variety of data sets.Comment: International Conference on 3D Vision (3DV), Qingdao, China, October 201