Image Processing

As one of the research directions at OLIVES Lab @ Georgia Tech, we focus on recognizing textures and materials in real-world images, which plays an important role in object recognition and scene understanding. Aiming at describing objects or scenes with more detailed information, we explore how to computationally characterize apparent or latent properties (e.g. surface smoothness) of materials, i.e., computational material characterization, which moves a step further beyond material recognition.

The Costas condition on a permutation matrix, expressed as row indices as elements of a vector c, can be expressed as A*c=b, where b is a vector of integers in which no element is zero.  A particular formulation of the matrix A allows a singular value decomposition in which the eigenvalues are squared integers and the eigenvalues may be scaled to vectors with all integer elements.  This is a database of the Costas constraint matrices A, the scaled eigenvectors, and the squared eigenvalues for orders 3 through 100.

Objective: No data currently exist on the reproducibility of photographic food records compared to diet diaries, two commonly used methods to measure habitual dietary intake. Our aim was to examine the reproducibility of diet diaries, photographic food records, and a novel electronic sensor, consisting of counts of chews and swallows using wearable sensors and video analysis, for estimating energy intake.

The supplementary files of our submitted TIFS paper: "CALPA-NET: Channel-pruning-assisted Deep Residual Network for Steganalysis of Digital Images".