Single‐shot High Dynamic Range Imaging Using Coded Electronic Shutter

Typical high dynamic range (HDR) imaging approaches based on multiple images have difficulties in handling moving objects and camera shakes, suffering from the ghosting effect and the loss of sharpness in the output HDR image. While there exist a variety of solutions for resolving such limitations, most of the existing algorithms are susceptible to complex motions, saturation, and occlusions. In this paper, we propose an HDR imaging approach using the coded electronic shutter which can capture a scene with row‐wise varying exposures in a single image. Our approach enables a direct extension of the dynamic range of the captured image without using multiple images, by photometrically calibrating rows with different exposures. Due to the concurrent capture of multiple exposures, misalignments of moving objects are naturally avoided with significant reduction in the ghosting effect. To handle the issues with under‐/over‐exposure, noise, and blurs, we present a coherent HDR imaging process where the problems are resolved one by one at each step. Experimental results with real photographs, captured using a coded electronic shutter, demonstrate that our method produces a high quality HDR images without the ghosting and blur artifacts.     

Random Accessible Mesh Compression Using Mesh Chartification

Previous mesh compression techniques provide decent properties such as high compression ratio, progressive decoding, and out-of-core processing. However, only a few of them supports the random accessibility in decoding, which enables the details of any specific part to be available without decoding other parts. This paper proposes an effective framework for the random accessibility of mesh compression. The key component of the framework is a wire-net mesh constructed from a chartification of the given mesh. Charts are compressed separately for random access to mesh parts and a wire-net mesh provides an indexing and stitching structure for the compressed charts. Experimental results show that random accessibility can be achieved with competent compression ratio, which is only a little worse than single-rate and comparable to progressive encoding. To demonstrate the merits of the framework, we apply it to process huge meshes in an out-of-core manner, such as out-of-core rendering and out-of-core editing.     

Scale‐aware Structure‐Preserving Texture Filtering

This paper presents a novel method to enhance the performance of structure‐preserving image and texture filtering. With conventional edge‐aware filters, it is often challenging to handle images of high complexity where features of multiple scales coexist. In particular, it is not always easy to find the right balance between removing unimportant details and protecting important features when they come in multiple sizes, shapes, and contrasts. Unlike previous approaches, we address this issue from the perspective of adaptive kernel scales. Relying on patch‐based statistics, our method identifies texture from structure and also finds an optimal per‐pixel smoothing scale. We show that the proposed mechanism helps achieve enhanced image/texture filtering performance in terms of protecting the prominent geometric structures in the image, such as edges and corners, and keeping them sharp even after significant smoothing of the original signal.     

Transitive mesh space of a progressive mesh

The paper investigates the set of all selectively refined meshes that can be obtained from a progressive mesh. We call the set the transitive mesh space of a progressive mesh and present a theoretical analysis of the space. We define selective edge collapse and vertex split transformations, which we use to traverse all selectively refined meshes in the transitive mesh space. We propose a complete selective refinement scheme for a progressive mesh based on the transformations and compare the scheme with previous selective refinement schemes in both theoretical and experimental ways. In our comparison, we show that the complete scheme always generates selectively refined meshes with smaller numbers of vertices and faces than previous schemes for a given refinement criterion. The concept of dual pieces of the vertices in the vertex hierarchy plays a central role in the analysis of the transitive mesh space and the design of selective edge collapse and vertex split transformations.     

Art‐photographic detail enhancement

We present a novel method for enhancing details in a digital photograph, inspired by the principle of art photography. In contrast to the previous methods that primarily rely on tone scaling, our technique provides a flexible tone transform model that consists of two operators: shifting and scaling. This model permits shifting of the tonal range in each image region to enable significant detail boosting regardless of the original tone. We optimize these shift and scale factors in our constrained optimization framework to achieve extreme detail enhancement across the image in a piecewise smooth fashion, as in art photography. The experimental results show that the proposed method brings out a significantly large amount of details even from an ordinary low‐dynamic range image.     

Motion retargeting and evaluation for VR-based training of free motions

Virtual reality (VR) has emerged as one of the important and effective tools for education and training. Most VR-based training systems are situation based, where the trainees are trained for discrete decision making in special situations presented by the VR environments. In contrast, this paper discusses the application of VR to a different class of training, for learning free motion, often required in sports and the arts. We propose a VR-based motion-training framework that contains an intuitive motion-guiding interface, posture-oriented motion retargeting, and an evaluation and advice scheme for corrective feedback. Applications of the proposed framework to simple fencing training and a dance imitation game are demonstrated.     

Photoluminescence plasmonic enhancement in InAs quantum dots coupled to gold nanoparticles

Photoluminescence enhancement due to dipole field from gold nanoparticles was observed at 77 K for GaAs capped InAs quantum dots. The gold nanoparticles were coupled to the surface of the cap layer by using dithiol ligands. The enhancement was investigated as a function of the GaAs capped layer thickness. An order of magnitude enhancement in the emission was observed in samples with a cap thickness of 12 nm. This enhancement however is drastically decreased in samples with a cap thickness of 200 nm. The observed enhancement is interpreted in terms of photon scattering from the large dipole scattering cross section.     

Highly Stretchable or Transparent Conductor Fabrication by a Hierarchical Multiscale Hybrid Nanocomposite

As is frequently seen in sci‐fi movies, future electronics are expected to ultimately be in the form of wearable electronics. To realize wearable electronics, the electric components should be soft, flexible, and even stretchable to be human‐friendly. An important step is presented toward realization of wearable electronics by developing a hierarchical multiscale hybrid nanocomposite for highly flexible, stretchable, or transparent conductors. The hybrid nanocomposite combines the enhanced mechanical compliance, electrical conductivity, and optical transparency of small CNTs (d ≈ 1.2 nm) and the enhanced electrical conductivity of relatively bigger Ag nanowire (d ≈ 150 nm) backbone to provide efficient multiscale electron transport path with Ag nanowire current backbone collector and local CNT percolation network. The highly elastic hybrid nanocomposite conductors and highly transparent flexible conductors can be mounted on any non‐planar or soft surfaces to realize human‐friendly electronics interface for future wearable electronics.