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Compressive Schlieren Deflectometry

Abstract: Schlieren deflectometry aims at characterizing the deflections undergone by refracted incident light rays at any surface point of a transparent object. For smooth surfaces, each surface location is actually associated with a sparse deflection map (or spectrum).

Consistent Iterative Hard Thresholding for Signal Declipping

Abstract: Clipping or saturation in audio signals is a very common problem in signal processing, for which, in the severe case, there is still no satisfactory solution. In such case, there is a tremendous loss of information, and traditional methods fail to appropriately recover the signal.

Quantized Iterative Hard Thresholding: Bridging 1-bit and High-Resolution Quantized Compressed Sensing

Abstract: In this work, we show that reconstructing a sparse signal from quantized compressive measurement can be achieved in an unified formalism whatever the (scalar) quantization resolution, i.e., from 1-bit to high resolution assumption.

Iterative Hypothesis Testing for Multi-object Tracking with Noisy/Missing Appearance Features

Abstract: This paper assumes prior detections of multiple targets at each time instant, and uses a graph-based approach to connect those de- tections across time, based on their position and appearance estimates.

Sparsity-driven optical deflection tomography with non-linear light ray propagation

Abstract: Optical deflection tomography based on phase-shifting Schlieren is well adapted for three-dimensional imaging of objects with large refractive index variations. We propose a reconstruction algorithm that takes into account light refraction and spatial sparsity of the sample.

TV-$\ell_{2}$ Refractive Index Map Reconstruction from Polar Domain Deflectometry

Compact Rotation Invariant Image Descriptors By Spectral Trimming

Abstract: Image descriptors are widely used in applications such as object recognition, pattern classification and image registration. The descriptors encode the local visual content of the image to provide a compact, robust and distinctive representation of objects.