Depth perception

بررسی تأثیر مشارکت ورزشی بر ادراک عمق سالمندان

Introduction and purpose: Number of elderly is increasing in the world and as they grow older the risk of falling increases, accordingly. Visual disturbances are among internal risky factors of falling and meanwhile depth perception attenuation as one king of visual disturbances has the highest relationship with their falling.  The aim of present investigation was to the effect of sports p...

Physiologically based models of binocular depth perception

Cartoon Effect and Ambient Illumination Based Depth Perception Assessment of 3D Video

Monitored 3-Dimensional (3D) video experience can be utilized as “feedback information” to fine tune the service parameters for providing a better service to the demanding 3D service customers. The 3D video experience which includes both video quality and depth perception is influenced by several contextual and content related factors (e.g., ambient illumination condition, content characteristi...

Higher resolution stimulus facilitates depth perception: MT+ plays a significant role in monocular depth perception

Today, we human beings are facing with high-quality virtual world of a completely new nature. For example, we have a digital display consisting of a high enough resolution that we cannot distinguish from the real world. However, little is known how such high-quality representation contributes to the sense of realness, especially to depth perception. What is the neural mechanism of processing su...

Visually Supporting Depth Perception in Angiography Imaging

In this paper we propose interactive visualization techniques which support the spatial comprehension of angiogram images by emphasizing depth information and introducing combined depth cues. In particular, we propose a depth based color encoding, two variations of edge enhancement and the application of a modified depth of field effect in order to enhance depth perception of complex blood vess...

Single-Image Depth Perception in the Wild

This paper studies single-image depth perception in the wild, i.e., recovering depth from a single image taken in unconstrained settings. We introduce a new dataset “Depth in the Wild” consisting of images in the wild annotated with relative depth between pairs of random points. We also propose a new algorithm that learns to estimate metric depth using annotations of relative depth. Compared to...