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In this paper we present a systematic approach to create smoothly varying images from a pair of photographs to facilitate enhanced awareness of the depth structure of a given scene. Since our system does not rely on sophisticated display technologies such as stereoscopy or auto-stereoscopy for depth awareness, it (a) is inexpensive and widely accessible, (b) does not suffer from vergence -accommodation fatigue, and (c) works entirely with monocular depth cues. Our approach enhances the depth awareness by optimizing across a number of features such as depth perception, optical flow, saliency, centrality, and disocclusion artifacts. We report the results of user studies that examine the relationship between depth perception, relative velocity, spatial perspective effects, and the positioning of the pivot point and use them when generating kinetic-depth images. We also present a novel depth re-mapping method guided by perceptual relationships based on the results of our user study. We validate our system by presenting a user study that compares the output quality of our proposed method against other existing alternatives on a wide range of images.

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We revisit the visibility problem, which is traditionally known in Computer Graphics and Vision fields as the process of computing a (potentially) visible set of primitives in the computational model of a scene. We propose a hybrid solution that uses a dry structure (in the sense of data reduction), a triangulation of the type Ja 1 , to accelerate the task of searching for visible primitives. We came up with a solution that is useful for real-time, on-line, interactive applications as 3D visualization. In such applications the main goal is to load the minimum amount of primitives from the scene during the rendering stage, as possible. For this purpose, our algorithm executes the culling by using a hybrid paradigm based on viewing-frustum, back-face culling and occlusion models. Results have shown substantial improvement over these traditional approaches if applied separately. This novel approach can be used in devices with no dedicated processors or with low processing power, as cell phones or embedded displays, or to visualize data through the Internet, as in virtual museums applications.