Long-Range Augmented Reality with Dynamic Occlusion Rendering.

Proper occlusion based rendering is very important to achieve realism in all indoor and outdoor Augmented Reality (AR) applications. This paper addresses the problem of fast and accurate dynamic occlusion reasoning by real objects in the scene for large scale outdoor AR applications. Conceptually, proper occlusion reasoning requires an estimate of depth for every point in augmented scene which is technically hard to achieve for outdoor scenarios, especially in the presence of moving objects.

Reducing bedtime physiological arousal levels using immersive audio-visual respiratory bio-feedback: a pilot study in women with insomnia symptoms.

Hyperarousal is a critical component of insomnia, particularly at bedtime when individuals are trying to fall asleep. The current study evaluated the effect of a novel, acute behavioral experimental manipulation (combined immersive audio-visual relaxation and biofeedback) in reducing bedtime physiological hyperarousal in women with insomnia symptoms. After a clinical/adaptation polysomnographic (PSG) night, sixteen women with insomnia symptoms had two random-order PSG nights: immersive audio-visual respiratory bio-feedback across the falling asleep period (manipulation night), and no pre-sleep arousal manipulation (control night).

Augmented Reality Binoculars.

In this paper we present an augmented reality binocular system to allow long range high precision augmentation of live telescopic imagery with aerial and terrain based synthetic objects, vehicles, people and effects. The inserted objects must appear stable in the display and must not jitter and drift as the user pans around and examines the scene with the binoculars. The design of the system is based on using two different cameras with wide field of view and narrow field of view lenses enclosed in a binocular shaped shell.

Spacetime Stereo and 3D Flow via Binocular Spatiotemporal Orientation Analysis.

This paper presents a novel approach to recovering estimates of 3D structure and motion of a dynamic scene from a sequence of binocular stereo images. The approach is based on matching spatiotemporal orientation distributions between left and right temporal image streams, which encapsulates both local spatial and temporal structure for disparity estimation. By capturing spatial and temporal structure in this unified fashion, both sources of information combine to yield disparity estimates that are naturally temporal coherent, while helping to resolve matches that might be ambiguous when either source is considered alone.

Action Spotting and Recognition Based on a Spatiotemporal Orientation Analysis.

This paper provides a unified framework for the interrelated topics of action spotting, the spatiotemporal detection and localization of human actions in video, and action recognition, the classification of a given video into one of several predefined categories. A novel compact local descriptor of video dynamics in the context of action spotting and recognition is introduced based on visual spacetime oriented energy measurements. This descriptor is efficiently computed directly from raw image intensity data and thereby forgoes the problems typically associated with flow-based features.

Spatiotemporal stereo and scene flow via stequel matching.

This paper is concerned with the recovery of temporally coherent estimates of 3D structure and motion of a dynamic scene from a sequence of binocular stereo images. A novel approach is presented based on matching of spatiotemporal quadric elements (stequels) between views, as this primitive encapsulates both spatial and temporal image structure for 3D estimation. Match constraints are developed for bringing stequels into correspondence across binocular views.