Temporal shape super-resolution by intra-frame motion encoding using high-fps structured light

One of the solutions of depth imaging of moving scene is to project a static pattern on the object and use just a single image for reconstruction. However, if the motion of the object is too fast with respect to the exposure time of the image sensor, patterns on the captured image are blurred and reconstruction fails. In this paper, we impose multiple projection patterns into each single captured image to realize temporal super resolution of the depth image sequences. With our method, multiple patterns are projected onto the object with higher fps than possible with a camera. In this case, the observed pattern varies depending on the depth and motion of the object, so we can extract temporal information of the scene from each single image. The decoding process is realized using a learning-based approach where no geometric calibration is needed. Experiments confirm the effectiveness of our method where sequential shapes are reconstructed from a single image. Both quantitative evaluations and comparisons with recent techniques were also conducted.Comment: 9 pages, Published at the International Conference on Computer Vision (ICCV 2017

Evaluation of depth-camera-systems for usage in semi-controlled assembly environments

With the availability of affordable depth-camera-systems like the Microsoft Kinect, Depth Imaging has seen a fast-growing number of applications in many different fields over the last years. Such systems can however be based on different measurement principles with widely differing parameters and hence are difficult to evaluate against a single benchmark. While accuracy and precision of depth-camera-systems inherently vary significantly with measuring distance and changing environments, and therefore impose heavy constraints on real world applications, they even allow for automated quality assurance in controlled environments. Context aware assistive systems in manual assembly environments push these boundaries by employing quality assurance in more open environments, where distracting influences by the worker or the work-space environment cannot be ruled out. The thesis concerns itself with the exploration and evaluation of different depth measuring approaches (e.g. Time of Flight, Structured Light, Stereo Vision) for usage in semi-controlled assembly environments. The still underexplored effects of material properties on measurements are experimentally evaluated and the resulting limitations of each approach for usage in assembly environments are discussed

ENHANCEMENTS TO THE MODIFIED COMPOSITE PATTERN METHOD OF STRUCTURED LIGHT 3D CAPTURE

The use of structured light illumination techniques for three-dimensional data acquisition is, in many cases, limited to stationary subjects due to the multiple pattern projections needed for depth analysis. Traditional Composite Pattern (CP) multiplexing utilizes sinusoidal modulation of individual projection patterns to allow numerous patterns to be combined into a single image. However, due to demodulation artifacts, it is often difficult to accurately recover the subject surface contour information. On the other hand, if one were to project an image consisting of many thin, identical stripes onto the surface, one could, by isolating each stripe center, recreate a very accurate representation of surface contour. But in this case, recovery of depth information via triangulation would be quite difficult. The method described herein, Modified Composite Pattern (MCP), is a conjunction of these two concepts. Combining a traditional Composite Pattern multiplexed projection image with a pattern of thin stripes allows for accurate surface representation combined with non-ambiguous identification of projection pattern elements. In this way, it is possible to recover surface depth characteristics using only a single structured light projection. The technique described utilizes a binary structured light projection sequence (consisting of four unique images) modulated according to Composite Pattern methodology. A stripe pattern overlay is then applied to the pattern. Upon projection and imaging of the subject surface, the stripe pattern is isolated, and the composite pattern information demodulated and recovered, allowing for 3D surface representation. In this research, the MCP technique is considered specifically in the context of a Hidden Markov Process Model. Updated processing methodologies explained herein make use of the Viterbi algorithm for the purpose of optimal analysis of MCP encoded images. Additionally, we techniques are introduced which, when implemented, allow fully automated processing of the Modified Composite Pattern image

Towards Intelligent Telerobotics: Visualization and Control of Remote Robot

Human-machine cooperative or co-robotics has been recognized as the next generation of robotics. In contrast to current systems that use limited-reasoning strategies or address problems in narrow contexts, new co-robot systems will be characterized by their flexibility, resourcefulness, varied modeling or reasoning approaches, and use of real-world data in real time, demonstrating a level of intelligence and adaptability seen in humans and animals. The research I focused is in the two sub-field of co-robotics: teleoperation and telepresence. We firstly explore the ways of teleoperation using mixed reality techniques. I proposed a new type of display: hybrid-reality display (HRD) system, which utilizes commodity projection device to project captured video frame onto 3D replica of the actual target surface. It provides a direct alignment between the frame of reference for the human subject and that of the displayed image. The advantage of this approach lies in the fact that no wearing device needed for the users, providing minimal intrusiveness and accommodating users eyes during focusing. The field-of-view is also significantly increased. From a user-centered design standpoint, the HRD is motivated by teleoperation accidents, incidents, and user research in military reconnaissance etc. Teleoperation in these environments is compromised by the Keyhole Effect, which results from the limited field of view of reference. The technique contribution of the proposed HRD system is the multi-system calibration which mainly involves motion sensor, projector, cameras and robotic arm. Due to the purpose of the system, the accuracy of calibration should also be restricted within millimeter level. The followed up research of HRD is focused on high accuracy 3D reconstruction of the replica via commodity devices for better alignment of video frame. Conventional 3D scanner lacks either depth resolution or be very expensive. We proposed a structured light scanning based 3D sensing system with accuracy within 1 millimeter while robust to global illumination and surface reflection. Extensive user study prove the performance of our proposed algorithm. In order to compensate the unsynchronization between the local station and remote station due to latency introduced during data sensing and communication, 1-step-ahead predictive control algorithm is presented. The latency between human control and robot movement can be formulated as a linear equation group with a smooth coefficient ranging from 0 to 1. This predictive control algorithm can be further formulated by optimizing a cost function. We then explore the aspect of telepresence. Many hardware designs have been developed to allow a camera to be placed optically directly behind the screen. The purpose of such setups is to enable two-way video teleconferencing that maintains eye-contact. However, the image from the see-through camera usually exhibits a number of imaging artifacts such as low signal to noise ratio, incorrect color balance, and lost of details. Thus we develop a novel image enhancement framework that utilizes an auxiliary color+depth camera that is mounted on the side of the screen. By fusing the information from both cameras, we are able to significantly improve the quality of the see-through image. Experimental results have demonstrated that our fusion method compares favorably against traditional image enhancement/warping methods that uses only a single image

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

COLOR MULTIPLEXED SINGLE PATTERN SLI

Structured light pattern projection techniques are well known methods of accurately capturing 3-Dimensional information of the target surface. Traditional structured light methods require several different patterns to recover the depth, without ambiguity or albedo sensitivity, and are corrupted by object movement during the projection/capture process. This thesis work presents and discusses a color multiplexed structured light technique for recovering object shape from a single image thus being insensitive to object motion. This method uses single pattern whose RGB channels are each encoded with a unique subpattern. The pattern is projected on to the target and the reflected image is captured using high resolution color digital camera. The image is then separated into individual color channels and analyzed for 3-D depth reconstruction through use of phase decoding and unwrapping algorithms thereby establishing the viability of the color multiplexed single pattern technique. Compared to traditional methods (like PMP, Laser Scan etc) only one image/one-shot measurement is required to obtain the 3-D depth information of the object, requires less expensive hardware and normalizes albedo sensitivity and surface color reflectance variations. A cosine manifold and a flat surface are measured with sufficient accuracy demonstrating the feasibility of a real-time system

System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns

A technique, associated system and program code, for retrieving depth information about at least one surface of an object. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the object; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration