Machine Learning in Sensors and Imaging

Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens

Toward New Ecologies of Cyberphysical Representational Forms, Scales, and Modalities

Research on tangible user interfaces commonly focuses on tangible interfaces acting alone or in comparison with screen-based multi-touch or graphical interfaces. In contrast, hybrid approaches can be seen as the norm for established mainstream interaction paradigms. This dissertation describes interfaces that support complementary information mediations, representational forms, and scales toward an ecology of systems embodying hybrid interaction modalities. I investigate systems combining tangible and multi-touch, as well as systems combining tangible and virtual reality interaction. For each of them, I describe work focusing on design and fabrication aspects, as well as work focusing on reproducibility, engagement, legibility, and perception aspects

deForm: An interactive malleable surface for capturing 2.5D arbitrary objects, tools and touch

We introduce a novel input device, deForm, that supports 2.5D touch gestures, tangible tools, and arbitrary objects through real-time structured light scanning of a malleable surface of interaction. DeForm captures high-resolution surface deformations and 2D grey-scale textures of a gel surface through a three-phase structured light 3D scanner. This technique can be combined with IR projection to allow for invisible capture, providing the opportunity for co-located visual feedback on the deformable surface. We describe methods for tracking fingers, whole hand gestures, and arbitrary tangible tools. We outline a method for physically encoding fiducial marker information in the height map of tangible tools. In addition, we describe a novel method for distinguishing between human touch and tangible tools, through capacitive sensing on top of the input surface. Finally we motivate our device through a number of sample applications

Evaluation of Physical Finger Input Properties for Precise Target Selection

The multitouch tabletop display provides a collaborative workspace for multiple users around a table. Users can perform direct and natural multitouch interaction to select target elements using their bare fingers. However, physical size of fingertip varies from one person to another which generally introduces a fat finger problem. Consequently, it creates the imprecise selection of small size target elements during direct multitouch input. In this respect, an attempt is made to evaluate the physical finger input properties i.e. contact area and shape in the context of imprecise selection

Functional-Material-Based Touch Interfaces for Multidimensional Sensing for Interactive Displays: A Review

Multidimensional sensing is a highly desired attribute for allowing human-machine interfaces (HMIs) to perceive various types of information from both users and the environment, thus enabling the advancement of various smart electronics/applications, e.g., smartphones and smart cities. Conventional multidimensional sensing is achieved through the integration of multiple discrete sensors, which introduces issues such as high energy consumption and high circuit complexity. These disadvantages have motivated the widespread use of functional materials for detecting various stimuli at low cost with low power requirements. This work presents an overview of simply structured touch interfaces for multidimensional (x-y location, force and temperature) sensing enabled by piezoelectric, piezoresistive, triboelectric, pyroelectric and thermoelectric materials. For each technology, the mechanism of operation, state-of-the-art designs, merits, and drawbacks are investigated. At the end of the article, the author discusses the challenges limiting the successful applications of functional materials in commercial touch interfaces and corresponding development trends

A Multi-functional Touch Panel for Multi-Dimensional Sensing in Interactive Displays

This thesis presents a flexible graphene/polyvinylidene difluoride (PVDF)/graphene sandwich for three-dimensional touch interactivity. Here, an x-y plane touch is sensed using graphene capacitive elements, while force sensing in the z-direction is by a piezoelectric PVDF/graphene sandwich. By employing different frequency bands for the capacitive- and force-induced electrical signals, the two stimuli are detected simultaneously, achieving three-dimensional touch sensing. Static force sensing and elimination of propagated stress are achieved by augmenting the transient piezo output with the capacitive touch, thus overcoming the intrinsic inability of the piezoelectric material in detecting non-transient force signals and avoiding force touch mis-registration by propagated stress. As a capacitive signal is important for force touch interpretation, optimization algorithms have been developed and implemented. With correlated double sampling (CDS) and spatial low-pass filtering (SLPF) based techniques, the signal-to-noise ratio (SNR) of the capacitive touch signal is boosted by 15.6 dB, indicating improved detection accuracy. In terms of the readout speed, fixed pattern and random pattern related down-sampling techniques are applied, giving rise to reductions in both readout time (11.3 ms) and power consumption (8.79 mW).China Scholarship Counci

A novel transparent and flexible pressure sensor for the human machine interface

The movement towards flexible and transparent electronics for use in displays, electronic skins, musical instruments and automotive industries, demands electrical components such as pressure sensors to evolve alongside circuitry and electrodes to ensure a fully flexible and transparent system. In the past, piezoresistive pressure sensors made with flexible electrodes have been fabricated, however, many of these systems are opaque. For the first time, we present a technology that exploits the natural self-assembly of polystyrene nanospheres to reproducibly create nanostructured materials to be used in optically transparent pressure sensors with sensing performance comparable to opaque industry standards. The performance of the piezoresistive pressure sensor relies on uniform elastic nano-dome arrays. A thin and homogeneous lining of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) renders the domes conductive and retains the transparent and flexible qualities of the underlying polymer. The film transparency is primarily dependant on PEDOT:PSS film thickness where transparencies as high as 79.3 \% are achieved for films of less than 100 nm in thickness. The sensors demonstrate a resistance response across the force range appropriate for all human machine interface interactions, which correspond here to 0.07 to 26 N. The fabrication process involves the creation of an electroactive mould which is used to create nanostructred polymer layers. To enable mould reuse and enhance process efficiency, an anti-adhesive treatment in the form of a self-assembled monolayer of alkanethiols has been developed. Three chain lengths for the alkanethiol of chemical structure H$_{3}$C-(CH$_{2}$)$_{n}$-SH where n = 3, 5, and 11 are investigated and SAM functionalisation is confirmed with XPS. Peel tests prove that all three are effective at preventing adhesion between the mould and PEDOT:PSS and the treatment is shown not to be detrimental to the polymer electrodeposition process. An adapted fabrication procedure with custom designed electrode housing enables larger samples to be created for prototype devices. A simple functional prototype in the form of a multi-pixel force sensor atop of an LED display is successfully designed and fabricated to highlight the technology for use at the human machine interface.Open Acces