1-bit news

OK, it’s been a while again, but here are the reasons for being silent.

1-bit LBD reconstruction is out!

Remember all those posts about LBDs, FREAKs, BRIEFs, and reconstructing images ? The latest version of tis work is out with a major feature: 1-bit quantized LBDs reconstruction. Yes, 1-bit !

To achieve this, we leverage some results from 1-bit Compressed Sensing thanks to my co-author Laurent Jacques.

So, the pre-print is on arxiv and on infoscience, and you can get the code from github.

And the abstract reads:

Local Binary Descriptors are becoming more and more popular for image matching tasks, especially when going mobile. While they are extensively studied in this context, their ability to carry enough information in order to infer the original image is seldom addressed.

In this work, we leverage an inverse problem approach to show that it is possible to directly reconstruct the image content from Local Binary Descriptors. This process relies on very broad assumptions besides the knowledge of the pattern of the descriptor at hand. This generalizes previous results that required either a prior learning database or non-binarized features.

Furthermore, our reconstruction scheme reveals differences in the way different Local Binary Descriptors capture and encode image information. Hence, the potential applications of our work are multiple, ranging from privacy issues caused by eavesdropping image keypoints streamed by mobile devices to the design of better descriptors through the visualization and the analysis of their geometric content.

ICPR’12, here I come!

I’ll be attending ICPR’12 next week to present the preliminary version of this work, but of course I’ll talk a bit about 1-bit ;-) If you’re attending the conference, it will be a great place to discuss about this work!

I’ll be silent again, but I’ll try to blog about the conference experience. See you there !