Real-time abandoned and stolen object detection based on spatio-temporal features in crowded scenes

Abandoned and stolen object detection is a challenging task due to occlusion, changes in lighting, large perspective distortion, and the similarity in appearance of different people. This paper presents real-time detection methods of abandoned and stolen objects in a complex video. The adaptive background modeling method is applied to stable tracking and the ghost image removing. To detect abandoned and stolen objects, the methods determine spatio-temporal relationship between moving people and suspicious drops. The space first detection method measures the distance between a moving object and a non-moving object in spatial change analysis. The time first detection method conducts temporal change analysis and then spatial change analysis. The potential abandoned object is classified as a definite abandoned or stolen object by two-level detection approach. The time-to-live timer is applied by adjusting several key parameters on each camera and environment. In experiments, we show the experimental results to evaluate our proposed methods using benchmark datasets.     

Effective pedestrian detection using deformable part model based on human model

Recently, pedestrian detection systems have become an important technology in the development of the advanced driver assistance system (ADAS) for the autonomous car. The histogram of oriented gradients (HOG) is currently the most basic algorithm for detecting pedestrians, but it treats the entire body of the pedestrian as one single feature. In other words, if the entire body of the pedestrian is not visible, the detection rate under HOG decreases markedly. To solve this problem, we propose a detection system using a deformable part model (DPM) that divides the pedestrian data into two parts using a latent support vector machine (SVM)-based machine-learning technique. Experimental results show that our approach achieves better performance in a detection system than the existing method. In practice, there are many occlusions in the environment in front of the vehicle. For example, the surrounding transport facilities, such as a car or another obstacle, can occlude a pedestrian. These occlusions can increase the false detection rate and cause difficulties during the detection process. Our proposed method uses a different approach and can easily be applied in real-world scenarios, regardless of occlusions.

     

Paternal and Maternal Information and Communication Technology Usage as Their Very Low Birth Weight Infants Transition Home From the NICU

Little is known about how differently mothers and fathers of very low birth weight (VLBW) infants use information and communication technology (ICT), especially during the vulnerable transition from the neonatal intensive care unit (NICU) to home. This study aims to qualitatively compare and contrast the two groups’ usage of technology. In-depth, semistructured phone interviews were conducted with 25 parents of 16 VLBW infants who had been hospitalized in the NICU. Grounded theory facilitated the understanding of interview data. This article discusses the patterns that emerged around the use of ICT between the two groups and discusses the implications for health information seeking, privacy and misinformation, online social networking, learning technology, choosing a health care provider, and health care communication.     

Range image denoising using a constrained local Gaussian model for 3D object query service in the smart space

A position and direction is a fundamental information for U-Business as an anywhere service. A mobile device camera image can increase an accuracy of the positioning, and a range image provides significant information in an occlusion scene. U-Business service queries the information with the range image for a precision position or a target object. We present a method for smoothing heavy noisy surfaces acquired by mobile 3D imaging devices to obtain the stable curvature. The smoothing is performed in a way that finds centers of probability distributions, which maximizes the likelihood of observed points with smooth constraints. The smooth constraints are derived from the unit tangent vector equality. This provides a way of obtaining smooth surfaces and stable curvatures. We achieve the smoothing by solving the regularized linear system. The unit tangent vector equality involves consideration of geometric symmetry, and it minimizes the variation of differential values that are a factor of curvatures. The proposed algorithm has two apparent advantages. The first thing is that the surfaces in a scene with various signals-to-noise ratio are smoothed, and then they can earn suitable curvatures. The second is that the proposed method works on heavy noisy surfaces, for example, a stereo camera image. Experiments on range images demonstrate that the proposed method yields the smooth surfaces from the input with various signals-to-noise ratio and the stable curvatures obtained from the smooth surfaces.     

A study of roll‐printing technology for TFT‐LCD fabrication

Abstract— Recently, potential breakthrough technologies for low‐cost processing of TFT‐LCDs and new process developments for flexible‐display fabrication have been widely studied. A roll‐printing process using etch‐resist material as a replacement for photolithographic patterning was investigated. The characterization of the properties of patterns formed in roll printing, a method to fabricate cliché plates for fine patterns, and the design of a new formulation for resist printing ink is reported. The pattern position accuracy, which is one of the most important issues for the successful application of printing processes in display manufacturing was studied and how it can be improved by optimizing the blanket roll structure is explained. New design rules for the layout of the thin‐film‐transistor array was derived to improve the compatibility of roll printing. As a result, a prototype 15‐in.‐XGA TFT‐LCD panel was fabricated by using printing processes to replace all the photolithographic patterning steps conventionally used.     

Touch‐screen panel integrated into 12.1‐in. a‐Si:H TFT‐LCD

Abstract— A touch‐screen‐panel (TSP) embedded 12.1‐in. LCD employing a standard existing a‐Si:H TFT‐LCD process has been successfully developed. Compared with conventional external touch‐screen panels, which use additional components to detect touch events, the new internal TSP exhibits a clearer image and improved touch feeling, as well as increased sensing speed using discrete sensing lines to enable higher‐speed sensing functions including handwriting. The new internal digital switching TSP can be fabricated with low cost because it does not require any additional process steps compared to a standard a‐Si:H TFT‐LCD.     

Electron‐beam deposition of MgO on plastic substrate and manufacturing flexible flat fluorescent lamp

Abstract— A flexible fluorescent lamp that utilizes the same plasma discharge mode as in PDPs has been manufactured. The structure of the flexible lamp is simple and easy to manufacture. All‐plastic materials including plastic substrates, barrier ribs (spacers), and sealants for low‐temperature manufacturing processing have been adopted except for the phosphor and MgO thin film. The MgO thin films were coated on the plastic substrates as a protection layer against the plasma discharge. The adhesion and biaxial texture of MgO thin film deposited on the plastic substrates, poly‐ethyle‐nenaphthalate (PEN) and polycarbonate (PC), at low temperature (100–180°C) has been characterized. The MgO film on PEN shows good adhesion under a repeated bending test. The manufactured flexible lamp consists of two plastic substrates of about 3 in. on the diagonal, barrier rib (spacer), and external ITO electrodes. The Ne‐Xe (5%) gas mixture at 100–200 Torr was used for the discharge gas. A maximum surface luminance of about 100 cd/m² was achieved for a 1 ‐kHz AC pulse.     

Incorporating affective customer needs for luxuriousness into product design attributes

In a highly competitive market, customers' product affection is a critical factor to product success. However, understanding customers' affective needs is difficult to grasp; product design practitioners often misunderstand what customers really want. In this study we report our experience in developing and using an affective design framework that identified critical affective features customers have on products and are systematically incorporated into product design attributes. To identify key affective features such as luxuriousness, we utilized the Kansei engineering methodology. This approach consists of three steps: (1) selecting related affective features and product design attributes through a comprehensive literature survey, expert panel opinion, and focus group interviews; (2) conducting evaluation experiments; and (3) developing Kansei models using multivariate statistical analysis and analyzing critical product design attributes. To demonstrate applicability of the proposed affective design framework, 30 customers and 30 product design practitioners participated in an evaluation experiment for car crash pads, and 44 customers and 20 designers participated in an evaluation experiment for two interior room products (wallpapers and flooring materials). The evaluation experiments were conducted via systematically developed questionnaires consisting of a 7‐point semantic differential scale and a 100‐point magnitude estimation scale. The results of the experiments were analyzed using principal component regression and quantification theory type I method. Using the analyzed survey data, the relationship between luxuriousness and related affective features and product design attributes were identified. This relationship indicated that there was a significant difference in the perception of luxuriousness between customers and designers. Consequently, it is expected that the results of this study could provide a foundation for developing affective products. © 2009 Wiley Periodicals, Inc.     

Approximate probabilistic optimization using exact-capacity-approximate-response-distribution (ECARD)

Probabilistic structural design deals with uncertainties in response (e.g. stresses) and capacity (e.g. failure stresses). The calculation of the structural response is typically expensive (e.g., finite element simulations), while the capacity is usually available from tests. Furthermore, the random variables that influence response and capacity are often disjoint. In previous work we have shown that this disjoint property can be used to reduce the cost of obtaining the probability of failure via Monte Carlo simulations. In this paper we propose to use this property for an approximate probabilistic optimization based on exact capacity and approximate response distributions (ECARD). In Approximate Probabilistic Optimization Using ECARD, the change in response distribution is approximated as the structure is re-designed while the capacity distribution is kept exact, thus significantly reducing the number of expensive response simulations. ECARD may be viewed as an extension of SORA (Sequential Optimization and Reliability Assessment), which proceeds with deterministic optimization iterations. In contrast, ECARD has probabilistic optimization iterations, but in each iteration, the response distribution is approximated so as not to require additional response calculations. The use of inexpensive probabilistic optimization allows easy incorporation of system reliability constraints and optimal allocation of risk between failure modes. The method is demonstrated using a beam problem and a ten-bar truss problem. The former allocates risk between two different failure modes, while the latter allocates risk between members. It is shown that ECARD provides most of the improvement from risk re-allocation that can be obtained from full probabilistic optimization.     

Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.