IMShare: instantly sharing your mobile landmark images by search-based reconstruction
Proceedings of the 20th ACM international conference on Multimedia
Towards feature-based situation assessment for airport apron video surveillance
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
Cloud-enabled privacy-preserving collaborative learning for mobile sensing
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
Cloud-Based image compression via subband-based reconstruction
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
| Hi-index | 0.00 |
This paper shows that an image can be approximately reconstructed based on the output of a blackbox local description software such as those classically used for image indexing. Our approach consists first in using an off-the-shelf image database to find patches that are visually similar to each region of interest of the unknown input image, according to associated local descriptors. These patches are then warped into input image domain according to interest region geometry and seamlessly stitched together. Final completion of still missing texture-free regions is obtained by smooth interpolation. As demonstrated in our experiments, visually meaningful reconstructions are obtained just based on image local descriptors like SIFT, provided the geometry of regions of interest is known. The reconstruction most often allows the clear interpretation of the semantic image content. As a result, this work raises critical issues of privacy and rights when local descriptors of photos or videos are given away for indexing and search purpose.