Computer-Vision-Based Vibration Tracking Using a Digital Camera: A Sparse-Optical-Flow-Based Target Tracking Method.

Computer-vision-based target tracking is a technology applied to a wide range of research areas, including structural vibration monitoring. However, current target tracking methods suffer from noise in digital image processing. In this paper, a new target tracking method based on the sparse optical flow technique is introduced for improving the accuracy in tracking the target, especially when the target has a large displacement.

DNA: Deeply Supervised Nonlinear Aggregation for Salient Object Detection.

Recent progress on salient object detection mainly aims at exploiting how to effectively integrate multiscale convolutional features in convolutional neural networks (CNNs). Many popular methods impose deep supervision to perform side-output predictions that are linearly aggregated for final saliency prediction. In this article, we theoretically and experimentally demonstrate that linear aggregation of side-output predictions is suboptimal, and it only makes limited use of the side-output information obtained by deep supervision.

Analysis on Mitigation of Visually Induced Motion Sickness by Applying Dynamical Blurring on a User's Retina.

Visually induced motion sickness (MS) experienced in a 3D immersive virtual environment (VE) limits the widespread use of virtual reality (VR). This paper studies the effects of a saliency detection-based approach on the reduction of MS when the display on a user's retina is dynamic blurred. In the experiment, forty participants were exposed to a VR experience under a control condition without applying dynamic blurring, and an experimental condition applying dynamic blurring.