The Majorana Demonstrator calibration system

The Collaboration is searching for the neutrinoless double-beta decay of the nucleus Ge. The is an array of germanium detectors deployed with the aim of implementing background reduction techniques suitable for a 1-ton Ge-based search. The ultra low-background conditions require regular calibrations to verify proper function of the detectors. Radioactive line sources can be deployed around the cryostats containing the detectors for regular energy calibrations. When measuring in low-background mode, these line sources have to be stored outside the shielding so they do not contribute to the background. The deployment and the retraction of the source are designed to be controlled by the data acquisition system and do not require any direct human interaction. In this paper, we detail the design requirements and implementation of the calibration apparatus, which provides the event rates needed to define the pulse-shape cuts and energy calibration used in the final analysis as well as data that can be compared to simulations

Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems

This study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram thresholding to extract the pixels of touch blobs obtained from scattered infrared lights captured by a video camera. The advantage of this automatic multilevel thresholding approach is its robustness and adaptability when dealing with various ambient lighting conditions and spurious infrared noises. To extract the connected components of these touch blobs, a connected-component analysis procedure is applied to the bright pixels acquired by the previous stage. After extracting the touch blobs from each of the captured image frames, a blob tracking and event recognition process analyzes the spatial and temporal information of these touch blobs from consecutive frames to determine the possible touch events and actions performed by users. This process also refines the detection results and corrects for errors and occlusions caused by noise and errors during the blob extraction process. The proposed blob tracking and touch event recognition process includes two phases. First, the phase of blob tracking associates the motion correspondence of blobs in succeeding frames by analyzing their spatial and temporal features. The touch event recognition process can identify meaningful touch events based on the motion information of touch blobs, such as finger moving, rotating, pressing, hovering, and clicking actions. Experimental results demonstrate that the proposed vision-based finger detection, tracking, and event identification system is feasible and effective for multi-touch sensing applications in various operational environments and conditions

HumanTop: a multi-object tracking tabletop

In this paper, a computer vision based interactive multi-touch tabletop system called HumanTop is introduced. HumanTop implements a stereo camera vision subsystem which allows not only an accurate fingertip tracking algorithm but also a precise touch-over-the-working surface detection method. Based on a pair of visible spectra cameras, a novel synchronization circuit makes the camera caption and the image projection independent from each other, providing the minimum basis for the development of computer vision analysis based on visible spectrum cameras without any interference coming from the projector. The assembly of both cameras and the synchronization circuit is not only capable of performing an ad-hoc version of a depth camera, but it also introduces the recognition and tracking of textured planar objects, even when contents are projected over them. On the other hand HumanTop supports the tracking of sheets of paper and ID-code markers. 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