Patch-based image synthesis methods have been successfully applied for various editing tasks on still images, videos and stereo pairs. In this work we extend patch-based synthesis to plenoptic images captured by consumer-level lenselet-based devices for interactive, efficient light field editing. In our method the light field is represented as a set of images captured from different viewpoints. We decompose the central view into different depth layers, and present it to the user for specifying the editing goals. Given an editing task, our method performs patch-based image synthesis on all affected layers of the central view, and then propagates the edits to all other views. Interaction is done through a conventional 2D image editing user interface that is familiar to novice users. Our method correctly handles object boundary occlusion with semi-transparency, thus can generate more realistic results than previous methods. We demonstrate compelling results on a wide range of applications such as hole-filling, object reshuffling and resizing, changing object depth, light field upscaling and parallax magnification.

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Figure 1: Given an input 3D anatomy template, we propose a system to simulate the effects of muscle, fat, and bone growth. This allows us to create a wide range of human body shapes. AbstractWe propose a method to create a wide range of human body shapes from a single input 3D anatomy template. Our approach is inspired by biological processes responsible for human body growth. In particular, we simulate growth of skeletal muscles and subcutaneous fat using physics-based models which combine growth and elasticity. Together with a tool to edit proportions of the bones, our method allows us to achieve a desired shape of the human body by directly controlling hypertrophy (or atrophy) of every muscle and enlargement of fat tissues. We achieve near-interactive run times by utilizing a special quasi-statics solver (Projective Dynamics) and by crafting a volumetric discretization which results in accurate deformations without an excessive number of degrees of freedom. Our system is intuitive to use and the resulting human body models are ready for simulation using existing physics-based animation methods, because we deform not only the surface, but also the entire volumetric model.

This article presents a navigation method for an autonomous underwater vehicle being recovered by a human-occupied vehicle. The autonomous underwater vehicle is considered to carry underwater navigation sensors such as ultra-short baseline, Doppler velocity log, and inertial navigation system. Using these sensors’ information, a navigation module combining the ultra-short baseline positioning and inertial positioning is established. In this study, there is assumed to be no communication between the autonomous underwater vehicle and human-occupied vehicle; thus, to obtain the autonomous underwater vehicle position in the inertial coordinate, a conjecture method to obtain the human-occupied vehicle coordinates is proposed. To reduce the error accumulation of autonomous underwater vehicle navigation, a method called one-step dead reckoning positioning is proposed, and the one-step dead reckoning positioning is treated as a correction to combine with ultra-short baseline positioning by a data fusion algorithm. One-step dead reckoning positioning is a positioning method based on the previous time-step coordinates of the autonomous underwater vehicle.

To meet the requirements of the adaptive optics systems with high bandwidths and large excursion angles, we propose a fast steering mirror (FSM) with an ultrahigh natural frequency and a large angular range. The proposed FSM is driven by a preloaded piezoelectric ceramic stack actuator (PCSA), which has a higher shear stress limit in the working direction. We describe the structure of the preloading device and analyze the stiffness improvement of the preloaded PCSA. Then we introduce the structure of the proposed FSM and perform theoretical analysis based on the established static model and dynamical model. We also build an experimental setup of the proposed FSM. The experimental results show that the angular range of the proposed FSM is up to 8.4 mrad, and its first natural frequency is 6660 Hz, which surpass the performances of current FSMs.

Fish interacting with biomimetic robotic fish is beneficial for animal behavior research, particularly in the study of collective behavior. Compared with passive-dragging robotic fish, self-propelled robotic fish floats in water, and its movement matches the flow field formed by the caudal fin oscillation, leading to more realistic interaction with animals. In this paper, we propose a self-propelled koi-mimicking robotic fish entity, develop a system for robotic fish and koi fish interaction, and conduct extensive experiments on quantity variation and parameter variation. The results showed that fish exhibited significantly lower proactivity when alone, and the most proactive case is one robotic fish interacting with two real fish. The experiments on parameter variation indicated that fish may respond more proactivity to robotic fish that swim with high frequency and low amplitude, but may also move together with high-frequency and high-amplitude swimming robotic fish. These findings could provide insights into fish collective behavior, guide the design of further fish-robot interaction experiments, and suggest directions for future improvements in goal-oriented robotic fish platforms.

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