DIY cardboard-based VR headset that enfolds a commodity smartphone is a popular means of achieving low cost immersive stereoscopic viewing experiences. However, existing applications for these devices have limited user-input capability, allowing mainly look-at control by head tilting. CardboardSense is a set of novel tap-gesture-based inputs that take advantage of the motion sensing capabilities already available in most smartphones. The key premise is that finger contacts with the cardboard surface produce incidental but detectable vibrations that can be reliably differentiated from typical user head motion. Moreover, tapping on different surface locations produces differentiable temporal signatures in the sensor signals. We present methods to extract and analyze these temporal patterns, and experimentally determine a set of tapping gestures that can be accurately recognized. Experimental results show promising potential for CardboardSense to extend the interactivity of future cardboard-based VR headset applications.

Previous research on impossible figures focuses extensively on single view modeling and rendering. Existing computer games that employ impossible figures as navigation maze for gaming either use a fixed third-person view with axonometric projection to retain the figure's impossibility perception, or simply break the figure's impossibility upon view changes. In this paper, we present a new approach towards 3D gaming with impossible figures, delivering for the first time navigation in 3D mazes constructed from impossible figures. Such result cannot be achieved by previous research work in modeling impossible figures. To deliver seamless gaming navigation and interaction, we propose i) a set of guiding principles for bringing out subtle perceptions and ii) a novel computational approach to construct 3D structures from impossible figure images and then to dynamically construct the impossible-figure maze subjected to user's view. In the end, we demonstrate and discuss our method with a variety of generic maze types.

Furniture typically consists of assemblies of elongated and planar parts that are connected together by glue, nails, hinges, screws, or other means that do not encourage disassembly and re-assembly. An alternative approach is to use an interlocking mechanism, where the component parts tightly interlock with one another. The challenge in designing such a network of interlocking joints is that local analysis is insufficient to guarantee global interlocking, and there is a huge number of joint combinations that require an enormous exploration effort to ensure global interlocking. In this paper, we present a computational solution to support the design of a network of interlocking joints that form a globally-interlocking furniture assembly. The key idea is to break the furniture complex into an overlapping set of small groups, where the parts in each group are immobilized by a local key, and adjacent groups are further locked with dependencies. The dependency among the groups saves the effort of exploring the immobilization of every subset of parts in the assembly, thus allowing the intensive interlocking computation to be localized within each small group. We demonstrate the effectiveness of our technique on many globally-interlocking furniture assemblies of various shapes and complexity.

Although we can interactively rotate a 3D projected high-dimensional geometry and observe its dynamic changes, this traditional visualization method is limited and highly sensitive to the choice of viewing direction. Parallel-coordinates plots supplement this visualization scenario by providing statistical analysis of the geometry for distinct pairs of co-dimensions. Such analysis results in visual signatures that embed geometric structures such as symmetry, and thus allows us to overview the status of the missing dimensions while exploring the projected geometry. This paper presents a blue-noise sampling approach for efficient construction of continuous parallel-coordinates plots of high-dimensional geometric surfaces defined by mathematical equations. We employ the parallel-coordinates plots with the embedded visual signatures to assist the interactive exploration of high-dimensional geometries, typically for 2-manifold embedded in 4-space. While we interactively explore the 3D projected geometry, we can observe dynamic changes on its visual signature. Various geometric properties can also be identified and visualized. Moreover, we can interactively brush the plots, and see their counterparts in the 3D projection. Assorted geometric properties such as curvature can further be used to enhance the visual signature.

Realistic facial animation is important in many graphics applications, like animated feature films and computer games, to enrich human computer interaction. In this paper, we propose a physically-based facial animation approach employing knowledge from the anatomy and biomechanics of human facial muscles. First, the 3D face mesh is generated automatically by commercial software and the facial skin is represented by a nonlinear mass-spring system which simulates realistic elastic dynamics of human dermis. Then, a structure skull is attached to fit the face mesh. A set of anatomically consistent facial muscles are incorporated to model the forces deforming the face mesh. Finally, we extend Waters' muscle model to improve the combination of multiple muscle actions and to generate realistic expression. Experiments show that our method is superior to the traditional geometric model and can achieve comparative results with the commercial software FaceGen.