The availability of commodity 3D extruder pen allows direct drawing of 3D wire sculptures for novice users, enabling many novel applications such as intuitive spatial intelligence development for school students. However, the lack of spatial and structural cues among individual pen strokes makes the 3D drawing process challenging, which often leads to highly distorted and even incomplete wire sculptures. We present a mixed reality system, called `WireDraw', to immersively guide the 3D drawing for easy wire sculpturing. The system design is based on novel 3D drawing principles and the subsequent optimization, making the stroke sequence of the wire model drawable and easy to draw. On-the-fly edits on unsatisfactory strokes are also allowed for creative design. We demonstrate the effectiveness of our system by testing on a variety of wire models and a user study. The results show that the visual guidance provided by our system is extremely helpful for drawing high-quality wire sculptures.

Due to the development of 3D sensing and modeling techniques, the state-of-the-art mixed reality devices such as Microsoft Hololens have the ability of digitalizing the physical world. This unique feature bridges the gap between virtuality and reality and largely elevates the user experience. Unfortunately, the current solution only performs well if the virtual contents complement the real scene. It can easily cause visual artifacts when the reality needs to be modified due to the virtuality (e.g., remove real objects to offer more space for virtual objects), a common scenario in mixed reality applications such as room redecoration and environment design. We present a novel system, called emph{SceneCtrl}, that allows the user to interactively edit the real scene sensed by Hololens, such that the reality can be adapted to suit virtuality. Our proof-of-concept prototype employs scene reconstruction and understanding to enable efficient editing such as deleting, moving, and copying real objects in the scene. We also demonstrate emph{SceneCtrl} on a number of example scenarios in mixed reality, verifying the enhanced experience by resolving conflicts between virtuality and reality.

Optical flow estimation is a difficult task given real-world video footage with camera and object blur. In this paper, we combine a 3D pose&position tracker with an RGB sensor allowing us to capture video footage together with 3D camera motion. We show that the additional camera motion information can be embedded into a hybrid optical flow framework by interleaving an iterative blind deconvolution and warping based minimization scheme. Such a hybrid framework significantly improves the accuracy of optical flow estimation in scenes with strong blur. Our approach yields improved overall performance against three state-of-the-art baseline methods applied to our proposed ground truth sequences, as well as in several other real-world sequences captured by our novel imaging system.