Camouflaging an Object from Many Viewpoints
Name
2014_camo.pdf
Description
Accepted version
Size
5.84 MB
Format
Unknown
Checksum (MD5)
091517ee08516c8683453757257ac45f
Author(s)
Owens, Andrew Hale
Barnes, Connelly
Flint, Alex
Singh, Hanumant
Freeman, William
Date Issued
June 2014
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Owens, Andrew, Barnes, Connelly, Flint, Alex, Singh, Hanumant and Freeman, William. 2014. "Camouflaging an Object from Many Viewpoints."
Version
Author's final manuscript
Abstract
© 2014 IEEE. We address the problem of camouflaging a 3D object from the many viewpoints that one might see it from. Given photographs of an object's surroundings, we produce a surface texture that will make the object difficult for a human to detect. To do this, we introduce several background matching algorithms that attempt to make the object look like whatever is behind it. Of course, it is impossible to exactly match the background from every possible viewpoint. Thus our models are forced to make trade-offs between different perceptual factors, such as the conspicuousness of the occlusion boundaries and the amount of texture distortion. We use experiments with human subjects to evaluate the effectiveness of these models for the task of camouflaging a cube, finding that they significantly outperform naïve strategies.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/cvpr.2014.350
