Issue No. 05 - May (2014 vol. 36)
Emmanuel dAngelo , Adv. Silicon S.A., Lausanne, Switzerland
Laurent Jacques , ELEN Dept., Univ. Catholique de Louvain (UCL), Louvain-la-Neuve, Belgium
Alexandre Alahi , Stanford Vision Lab., Stanford Univ., Stanford, CA, USA
Pierre Vandergheynst , Signal Process. Labs. (LTS2), Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland
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.
image reconstruction, image coding, image matching,geometric content visualization, local binary descriptor inversion, image matching tasks, original image, inverse problem approach, image content reconstruction, descriptor pattern knowledge, image information encoding, image information capturing, privacy issues, eavesdropping image keypoints, mobile devices, geometric content analysis,Image reconstruction, Vectors, Databases, Minimization, Mobile communication, Privacy, Benchmark testing,Reconstruction, Computer vision, Image Processing and Computer Vision, Feature representation, Representations, data structures, and transforms,privacy, Computer vision, inverse problems, image reconstruction, BRIEF, FREAK
Emmanuel dAngelo, Laurent Jacques, Alexandre Alahi, Pierre Vandergheynst, "From Bits to Images: Inversion of Local Binary Descriptors", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 36, no. , pp. 874-887, May 2014, doi:10.1109/TPAMI.2013.228