A multi-projector CAVE system with commodity hardware and gesture-based interaction

Spatially-immersive systems such as CAVEs provide users with surrounding worlds by projecting 3D models on multiple screens around the viewer. Compared to alternative immersive systems such as HMDs, CAVE systems are a powerful tool for collaborative inspection of virtual environments due to better use of peripheral vision, less sensitivity to tracking errors, and higher communication possibilities among users. Unfortunately, traditional CAVE setups require sophisticated equipment including stereo-ready projectors and tracking systems with high acquisition and maintenance costs. In this paper we present the design and construction of a passive-stereo, four-wall CAVE system based on commodity hardware. Our system works with any mix of a wide range of projector models that can be replaced independently at any time, and achieves high resolution and brightness at a minimum cost. The key ingredients of our CAVE are a self-calibration approach that guarantees continuity across the screen, as well as a gesture-based interaction approach based on a clever combination of skeletal data from multiple Kinect sensors.Preprin

Pictures in Your Mind: Using Interactive Gesture-Controlled Reliefs to Explore Art

Tactile reliefs offer many benefits over the more classic raised line drawings or tactile diagrams, as depth, 3D shape, and surface textures are directly perceivable. Although often created for blind and visually impaired (BVI) people, a wider range of people may benefit from such multimodal material. However, some reliefs are still difficult to understand without proper guidance or accompanying verbal descriptions, hindering autonomous exploration. In this work, we present a gesture-controlled interactive audio guide (IAG) based on recent low-cost depth cameras that can be operated directly with the hands on relief surfaces during tactile exploration. The interactively explorable, location-dependent verbal and captioned descriptions promise rapid tactile accessibility to 2.5D spatial information in a home or education setting, to online resources, or as a kiosk installation at public places. We present a working prototype, discuss design decisions, and present the results of two evaluation studies: the first with 13 BVI test users and the second follow-up study with 14 test users across a wide range of people with differences and difficulties associated with perception, memory, cognition, and communication. The participant-led research method of this latter study prompted new, significant and innovative developments

End-to-end Projector Photometric Compensation

Projector photometric compensation aims to modify a projector input image such that it can compensate for disturbance from the appearance of projection surface. In this paper, for the first time, we formulate the compensation problem as an end-to-end learning problem and propose a convolutional neural network, named CompenNet, to implicitly learn the complex compensation function. CompenNet consists of a UNet-like backbone network and an autoencoder subnet. Such architecture encourages rich multi-level interactions between the camera-captured projection surface image and the input image, and thus captures both photometric and environment information of the projection surface. In addition, the visual details and interaction information are carried to deeper layers along the multi-level skip convolution layers. The architecture is of particular importance for the projector compensation task, for which only a small training dataset is allowed in practice. Another contribution we make is a novel evaluation benchmark, which is independent of system setup and thus quantitatively verifiable. Such benchmark is not previously available, to our best knowledge, due to the fact that conventional evaluation requests the hardware system to actually project the final results. Our key idea, motivated from our end-to-end problem formulation, is to use a reasonable surrogate to avoid such projection process so as to be setup-independent. Our method is evaluated carefully on the benchmark, and the results show that our end-to-end learning solution outperforms state-of-the-arts both qualitatively and quantitatively by a significant margin.Comment: To appear in the 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Source code and dataset are available at https://github.com/BingyaoHuang/compenne

Laser Pointer Tracking in Projector-Augmented Architectural Environments

We present a system that applies a custom-built pan-tilt-zoom camera for laser-pointer tracking in arbitrary real environments. Once placed in a building environment, it carries out a fully automatic self-registration, registrations of projectors, and sampling of surface parameters, such as geometry and reflectivity. After these steps, it can be used for tracking a laser spot on the surface as well as an LED marker in 3D space, using inter-playing fisheye context and controllable detail cameras. The captured surface information can be used for masking out areas that are critical to laser-pointer tracking, and for guiding geometric and radiometric image correction techniques that enable a projector-based augmentation on arbitrary surfaces. We describe a distributed software framework that couples laser-pointer tracking for interaction, projector-based AR as well as video see-through AR for visualizations with the domain specific functionality of existing desktop tools for architectural planning, simulation and building surveying

Real-time 3D Face Recognition using Line Projection and Mesh Sampling

The main contribution of this paper is to present a novel method for automatic 3D face recognition based on sampling a 3D mesh structure in the presence of noise. A structured light method using line projection is employed where a 3D face is reconstructed from a single 2D shot. The process from image acquisition to recognition is described with focus on its real-time operation. Recognition results are presented and it is demonstrated that it can perform recognition in just over one second per subject in continuous operation mode and thus, suitable for real time operation

Kinect Range Sensing: Structured-Light versus Time-of-Flight Kinect

Recently, the new Kinect One has been issued by Microsoft, providing the next generation of real-time range sensing devices based on the Time-of-Flight (ToF) principle. As the first Kinect version was using a structured light approach, one would expect various differences in the characteristics of the range data delivered by both devices. This paper presents a detailed and in-depth comparison between both devices. In order to conduct the comparison, we propose a framework of seven different experimental setups, which is a generic basis for evaluating range cameras such as Kinect. The experiments have been designed with the goal to capture individual effects of the Kinect devices as isolatedly as possible and in a way, that they can also be adopted, in order to apply them to any other range sensing device. The overall goal of this paper is to provide a solid insight into the pros and cons of either device. Thus, scientists that are interested in using Kinect range sensing cameras in their specific application scenario can directly assess the expected, specific benefits and potential problem of either device.Comment: 58 pages, 23 figures. Accepted for publication in Computer Vision and Image Understanding (CVIU

Handheld 3D scanning system for in-vivo imaging of skin cancer

Postprint (published version

Calibration Methods for Head-Tracked 3D Displays

Head-tracked 3D displays can provide a compelling 3D effect, but even small inaccuracies in the calibration of the participant’s viewpoint to the display can disrupt the 3D illusion. We propose a novel interactive procedure for a participant to easily and accurately calibrate a head-tracked display by visually aligning patterns across a multi-screen display. Head-tracker measurements are then calibrated to these known viewpoints. We conducted a user study to evaluate the effectiveness of different visual patterns and different display shapes. We found that the easiest to align shape was the spherical display and the best calibration pattern was the combination of circles and lines. We performed a quantitative camera-based calibration of a cubic display and found visual calibration outperformed manual tuning and generated viewpoint calibrations accurate to within a degree. Our work removes the usual, burdensome step of manual calibration when using head-tracked displays and paves the way for wider adoption of this inexpensive and effective 3D display technology