GTC ON-DEMAND

 
SEARCH SESSIONS
SEARCH SESSIONS

Search All
 
Refine Results:
 
Year(s)

SOCIAL MEDIA

EMAIL SUBSCRIPTION

 
 

GTC ON-DEMAND

Computer Vision
Presentation
Media
Computational Zoom: A Framework to Manipulate Image Composition in Post-Capture
Abstract:
Telling the right story with a picture requires the ability to create the right composition. Two critical parameters controlling composition are the camera position and the focal length of the lens. The traditional paradigm to capture a picture is for a photographer to mentally visualize the desired result, select the capture parameters to produce it, and finally take the photograph, thus committing to a particular composition. To break this paradigm, we introduce computational zoom, a framework that allows a photographer to manipulate several aspects of composition in post-capture. Our approach also defines a multi-perspective camera that can generate compositions that are not attainable with a physical lens. Our framework requires a high-quality estimation of the scene's depth. Existing methods to estimate 3D information generally fail to produce dense maps, or sacrifice depth uncertainty to avoid missing estimates. We propose a novel GPU-based depth estimation technique that outperforms the state of the art in terms of quality, while ensuring that each pixel is associated with a depth value.
 
Topics:
Computer Vision, Video & Image Processing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8253
Streaming:
Share: