Optical recognition of modern and Roman coins

The recently granted EU project COINS aims to contribute substantially to the fight against illegal trade and theft of coins that appears to be a major part of the illegal antiques market. A central component of the permanent identification and traceability of coins is the underlying image recognition technology. However, currently available algorithms focus basically on the recognition of modern coins. To date, no optical recognition system for ancient coins has been successfully researched. It is a challenging task to work with medieval coins since they are – unlike modern coins – not mass manufactured. In this project, the recognition of coins will be based on new algorithms of pattern recognition and image processing, in a field – classification and identification of medieval coins – as yet unexplored. Since the project recently started, preliminary results and work already performed in this field are presented and discussed

Human Action Recognition in Egocentric Perspective Using 2D Object and Hands Pose

Egocentric action recognition is essential for healthcare and assistive technology that relies on egocentric cameras because it allows for the automatic and continuous monitoring of activities of daily living (ADLs) without requiring any conscious effort from the user. This study explores the feasibility of using 2D hand and object pose information for egocentric action recognition. While current literature focuses on 3D hand pose information, our work shows that using 2D skeleton data is a promising approach for hand-based action classification, might offer privacy enhancement, and could be less computationally demanding. The study uses a state-of-the-art transformer-based method to classify sequences and achieves validation results of 94%, outperforming other existing solutions. The accuracy of the test subset drops to 76%, indicating the need for further generalization improvement. This research highlights the potential of 2D hand and object pose information for action recognition tasks and offers a promising alternative to 3D-based methods

Strong Optomechanical Squeezing of Light

We create squeezed light by exploiting the quantum nature of the mechanical interaction between laser light and a membrane mechanical resonator embedded in an optical cavity. The radiation pressure shot noise (fluctuating optical force from quantum laser amplitude noise) induces resonator motion well above that of thermally driven motion. This motion imprints a phase shift on the laser light, hence correlating the amplitude and phase noise, a consequence of which is optical squeezing. We experimentally demonstrate strong and continuous optomechanical squeezing of 1.7 +/- 0.2 dB below the shot noise level. The peak level of squeezing measured near the mechanical resonance is well described by a model whose parameters are independently calibrated and that includes thermal motion of the membrane with no other classical noise sources.Comment: 12 pages, 8 figure

Improved motion segmentation based on shadow detection

In this paper, we discuss common colour models for background subtraction and problems related to their utilisation are discussed. A novel approach to represent chrominance information more suitable for robust background modelling and shadow suppression is proposed. Our method relies on the ability to represent colours in terms of a 3D-polar coordinate system having saturation independent of the brightness function; specifically, we build upon an Improved Hue, Luminance, and Saturation space (IHLS). The additional peculiarity of the approach is that we deal with the problem of unstable hue values at low saturation by modelling the hue-saturation relationship using saturation-weighted hue statistics. The effectiveness of the proposed method is shown in an experimental comparison with approaches based on RGB, Normalised RGB and HSV

3D Acquisition of Archaeological Ceramics and Web-Based 3D Data Storage

Motivated by the requirements of modern archaeology, we are developing an automated system for archaeological classification and reconstruction of ceramics. The goal is to create a tool that satisfies the criteria of accuracy, performance (findings/hour), robustness, transportability, overall costs, and careful handling of the findings. Following our previous work, we present new achievements on the documentation steps for 3D acquisition, 3D data processing, and 3D reconstruction. We have improved our system so that it can handle large quantities of ceramic fragments efficiently and computes a more robust orientation of a fragment. In order to store the sherd data acquired and hold all the information necessary to reconstruct a complete vessel, a database for archaeological fragments was developed. We will demonstrate practical experiments and results undertaken onsite at different excavations in Israel and Peru

In-Situ Dual-Port Polarization Contrast Imaging of Faraday Rotation in a High Optical Depth Ultracold 87Rb Atomic Ensemble

We study the effects of high optical depth and density on the performance of a light-atom quantum interface. An in-situ imaging method, a dual-port polarization contrast technique, is presented. This technique is able to compensate for image distortions due to refraction. We propose our imaging method as a tool to characterize atomic ensembles for high capacity spatial multimode quantum memories. Ultracold dense inhomogeneous Rubidium samples are imaged and we find a resonant optical depth as high as 680 on the D1 line. The measurements are compared with light-atom interaction models based on Maxwell-Bloch equations. We find that an independent atom assumption is insufficient to explain our data and present corrections due to resonant dipole-dipole interactions