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Projector deblurring is an important technology for dynamic projection mapping (PM), where the distance between a projector and a projection surface changes in time. However, conventional projector deblurring techniques do not support dynamic PM because they need to project calibration patterns to estimate the amount of defocus blur each time the surface moves. We present a deep neural network that can compensate for defocus blur in dynamic PM. The primary contribution of this paper is a unique network structure that consists of an extractor and a generator. The extractor explicitly estimates a defocus blur map and a luminance attenuation map. These maps are then injected into the middle layers of the generator network that computes the compensation image. We also propose a pseudo-projection technique for synthesizing physically plausible training data, considering the geometric misregistration that potentially happens in actual PM systems. We conducted simulation and actual PM experiments and confirmed that: (1) the proposed network structure is more suitable than a simple, more general structure for projector deblurring; (2) the network trained with the proposed pseudo-projection technique can compensate projection images for defocus blur artifacts in dynamic PM; and (3) the network supports the translation speed of the surface movement within a certain range that covers normal human motions.

The appearance of fabric motion is suggested to affect the human perception of bending stiffness. This study presents a novel spatial augmented reality, or projection mapping, approach that can visually manipulate the perceived bending stiffness of a fabric. Particularly, we proposed a flow enhancement method that can change the apparent fabric motion by using a simple optical flow analysis technique rather than complex physical simulations for interactive applications. Through a psychophysical experiment, we investigated the relationship between the magnification factor of our flow enhancement and the perceived bending stiffness of a fabric. Furthermore, we constructed a prototype application system that allows users to control the stiffness of a fabric without changing the actual physical fabric. By evaluating the prototype, we confirmed that the proposed technique can manipulate the perceived stiffness of various materials (i.e., cotton, polyester, and mixed cotton and linen) at an average accuracy of 90.3 percent.

Nature evolves structures like honeycombs at optimized performance with limited material. These efficient structures can be artificially created with the collaboration of structural topology optimization and additive manufacturing. However, the extensive computation cost of topology optimization causes low mesh resolution, long solving time, and rough boundaries that fail to match the requirements for meeting the growing personal fabrication demands and printing capability. Therefore, we propose the neural synthesizing topology optimization that leverages a self‐supervised coordinate‐based network to optimize structures with significantly shorter computation time, where the network encodes the structural material layout as an implicit function of coordinates. Continuous solution space is further generated from optimization tasks under varying boundary conditions or constraints for users' instant inference of novel solutions. We demonstrate the system's efficacy for a broad usage scenario through numerical experiments and 3D printing. [ABSTRACT FROM AUTHOR]

In this special issue of IEEE Transactions on Visualization and Computer Graphics (TVCG), we are pleased to present the journal papers from the 21st IEEE International Symposium on Mixed and Augmented Reality (ISMAR 2022), which will be held as a hybrid conference between October 17 and 21, 2022 in Singapore. ISMAR continues the over twenty year long tradition of IWAR, ISMR, and ISAR, and is the premier conference for Mixed and Augmented Reality in the world. [ABSTRACT FROM AUTHOR]

In this special issue of IEEE Transactions on Visualization and Computer Graphics (TVCG), we are pleased to present a subset of papers from the 29th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2022), held virtually March 12-16, 2022, in Christchurch, New Zealand. [ABSTRACT FROM AUTHOR]

This paper presents Limpid Desk that supports document search on a physical desktop by making the upper layer of a document stack transparent in a projection-based mixed reality environment. A user can visually access a lower-layer document without physically removing the upper documents. This is accomplished by superimposition of cover textures of lower-layer documents on the upper documents by projected imagery. This paper introduces a method of generating projection images that make physical documents transparent. Furthermore, a touch sensing method based on thermal image processing is proposed for the system's input interface. Areas touched by a user on physical documents can be detected without any user-worn or handheld devices. This interface allows a user to select a stack to be made transparent by a simple touch gesture. Three document search support techniques are realized using the system. User studies are conducted, and the results show the effectiveness of the proposed techniques. [ABSTRACT FROM AUTHOR]

This article focuses on real-time image correction techniques that enable projector-camera systems to display images onto screens that are not optimized for projections, such as geometrically complex, coloured and textured surfaces. It reviews hardware-accelerated methods like pixel-precise geometric warping, radiometric compensation, multi-focal projection and the correction of general light modulation effects. Online and offline calibration as well as invisible coding methods are explained. Novel attempts in super-resolution, high-dynamic range and high-speed projection are discussed. These techniques open a variety of new applications for projection displays. Some of them will also be presented in this report. [ABSTRACT FROM AUTHOR]

In this special issue of IEEE Transactions on Visualization and Computer Graphics (TVCG), we are pleased to present the journal papers from the 20th IEEE International Symposium on Mixed and Augmented Reality (ISMAR 2021), which will be held as a virtual conference between October 4 and 8, 2021. ISMAR continues the over twenty year long tradition of IWAR, ISMR, and ISAR, and is the premier conference for Mixed and Augmented Reality in the world. [ABSTRACT FROM AUTHOR]