Year: 2014
Type: article
Abstract: We present the general idea of a computer vision structure-from-motion framework that makes use of sensor fusion to provide very accurate and efficient multi-view reconstruction results that can capture internal geometry. Given the increased ubiquity and cost-effectiveness of embedding sensors, such as positional sensors, into objects, it has become feasible to fuse such sensor data and camera-acquired data to vastly improve reconstruction quality and enable a number of novel applications for structure-from-motion. Application areas, which require very high accuracy, include medicine, robotics, security, and additive manufacturing (3D printing). Specific examples and initial results are discussed, followed by a discussion on proposed future work.
Institution: University of California, Davis
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2262383884