A Review of An Interactive Augmented Reality Customization Clothing System Using Finger Tracking Techniques as Input Device

This paper mainly focuses on the review of applications in Augmented Reality (AR) technology in the field of clothing customization using finger tracking techniques as input device. Review the influence and role of AR technology in the clothing customization industry. A comparative analysis of the technological advances and technical deficiencies embodied in the virtual fitting software developed by the world in the past 10 years using AR technology. Through research and comparison, a personalized clothing customization system based on AR technology is proposed. The system can enhance people’s experience and interaction with the fashion design process and improve the satisfaction of clothing customization using finger techniques as input device

Vision-based dynamic hand gesture recognition techniques and applications: A review

Hand gesture recognition is an area in computer science that focuses on utilizing mathematical algorithms to analyze human gestures. The aim of this study is to perform a review evaluating related input devices, techniques, limitations and problems of dynamic hand gesture recognition using vision-based methods. More precisely, the hand gesture recognition process is divided into four stages: (a) input image, (b) segmentation, (c) feature extraction and (d) classification/recognition. Gesture control is the ability to acknowledge and interpret human body movements using a variety of gestures or motions made in the air by interacting and controlling devices without having the need to physically touch them. The Single Camera, Leap Motion Controller (LMC) and Microsoft Kinect are the three vision-based hand gestures devices that are compared in this review paper. We found out that the Single Camera is able to perform and achieve an accuracy rate of more than 95%. Besides, this paper not only is able to differentiate and compare the accuracy rate between the input devices, but also between the techniques applied which consists of (a) Hidden Markov Model, (b) Dynamic Time warping and (c) Neural Network including their advantages as well as the disadvantages. The applications that are used in vision-based dynamic hand gesture recognition are presented

The intelligence between the influence of AR technical ideological and political courses on the different characteristics of college students

In the contemporary educational ecosystem, Augmented Reality (AR) technology is marking its prominence across diverse disciplines globally, and China has been an active adopter. By integrating AR, educators, especially those handling ideological and political courses, can elevate their teaching methodologies, rendering them more interactive and engaging. For instance, traditionally static textbook content can be transformed into interactive elements, allowing students a tactile experience, while intricate theoretical constructs can be elucidated through dynamic video demonstrations. Such immersive approaches not only enhance comprehension but also significantly boost students’ enthusiasm and classroom involvement. Beyond mere content delivery, AR opens up avenues for innovative classroom exercises and evaluations. Within the framework of ideological and political courses, students, by leveraging AR, can simulate real-world scenarios, ensuring that knowledge transcends theory and is solidified through practical application. The essence of our research underscores the pivotal role of AR in rejuvenating pedagogical strategies, fostering improved learning outcomes, and ensuring a holistic understanding of intricate ideological and political concepts. Keywords: five major personalities; AR learning system; ideological and political learning analysis

A comparative study of interactive segmentation with different number of strokes on complex images

Interactive image segmentation is the way to extract an object of interest with the guidance of the user. The guidance from the user is an iterative process until the required object of interest had been segmented. Therefore, the input from the user as well as the understanding of the algorithms based on the user input has an essential role in the success of interactive segmentation. The most common user input type in interactive segmentation is using strokes. The different number of strokes are utilized in each different interactive segmentation algorithms. There was no evaluation of the effects on the number of strokes on this interactive segmentation. Therefore, this paper intends to fill this shortcoming. In this study, the input strokes had been categorized into single, double, and multiple strokes. The use of the same number of strokes on the object of interest and background on three interactive segmentation algorithms: i) Nonparametric Higher-order Learning (NHL), ii) Maximal Similarity-based Region Merging (MSRM) and iii) Graph-Based Manifold Ranking (GBMR) are evaluated, focusing on the complex images from Berkeley image dataset. This dataset contains a total of 12,000 test color images and ground truth images. Two types of complex images had been selected for the experiment: image with a background color like the object of interest, and image with the object of interest overlapped with other similar objects. This can be concluded that, generally, more strokes used as input could improve image segmentation accuracy

Design and application of performance evaluation model of school education informatization based on artificial intelligence mode

Educational informationization is an important part of educational reform. The performance evaluation of educational informationization plays an important role in promoting the development of informationization. Therefore, a performance evaluation model of school education informatization based on artificial intelligence mode is put forward. First, the current situation of school education informatization evaluation is briefly described, summarizing the artificial intelligence technology. The evaluation model of education informatization based on artificial intelligence is established, the performance evaluation index of school education informatization analyzed in detail. The index meets the requirement of input data through quantification and normalization, and the process of performance evaluation is designed. Feasibility and stability of the evaluation method are confirmed by the performance evaluation of school education informatization and the error analysis of the test results

A brief comparative of indoor positioning system

Indoor positioning systems is one of the most challenging future for Internet of Things (IoT) applications, especially in smart buildings. On spatial nature of tasks in a built environment, target users localize spatial location with a frame of reference (for example, way-finding location based services at airport using indoor positioning systems). This paper presents a brief study of various Indoor Positioning System (IPS). Comparison of the IPS are carried out and this study finds that the most ideal for current technology used is iBeacon, (BLE) for indoor positioning

System Usability Scale Formula as Alternative for Calculating Composite Score of Likert-type Items

Since its conception, Likert Scales have been used extensively in various fields. There are many ways to describe data obtained with Likert scales. In Human Factors research, System Usability Scale (SUS) is a widely adapted Likert Scale instrument to assess the usability of various products and systems. Researchers often have the tendency to modify SUS to fit their context of use, leading to various versions of SUS. Calculation of the composite score for SUS instrument does not involve computation of arithmetic mean/sum and re-coding of statements. SUS formula obtains the score for each Likert-type items and convert them into a single scale range from 0 to 100. Although SUS is a popular instrument, there is no formula introduced to facilitate the calculation of scale. This article aims to introduce a formula to facilitate the calculation of various versions of SUS with different number of items, number of positive and negative statements, as well as scale size. Although primarily meant for SUS practitioners, the formula presented can be used for any instrument adapting Likert-type items should the researchers decide to transform responses into 0-100 scale instead of computation of mean or sum for various statistical analyses. The controversial computation of mean for Likert Scales has been subjected to decades of debate. This article demonstrates an alternate method to calculate composite score of Likert-type items based on calculation of SUS. Results show the formula yield the same results and perfect relationship with mean and sum for various tests, indicating it can be used as an alternative to mean and sum as a composite score of Likert-types items

Extracting Relevant Information Using Handheld Augmented Reality

Augmented Reality (AR) technology is being incorporated into education materials to attract students and to make the learning experience more engaging. This study focuses on the development of 3D object, audio-visual and interaction in Handheld AR. This research aims to bridge that gap using Handheld AR for a magazine, which allows students to get an overview and interact with the 3D model of the campus, view general information and events of the university. This magazine also benefits students that live outside Dhaka, who are unable to visit the campus beforehand. The users can use their Android phone camera for real-time video capture and render virtual objects in the augmented environment through Vuforia and Unity engine integration. To evaluate system effectiveness and user satisfaction, a survey is conducted. The survey consists of user background information, functionality tests and a user feedback questionnaire. The outcome of the survey shows satisfactory of the successful implementation of 3D and multimedia modules. This paper also discusses the future scopes and summarizes how to extract relevant information for students to gain knowledge and get entertainment by using handheld AR

Human motion recognition based on Kinect sensor and leap motion controller

Augmented reality (AR) is an interactive experience of a real-world environment where objects reside in the real world are enhanced by computer-generated perceptual information. In essence, emulating and altering reality that include, in relatively real-time and precision, position and motion tracking (sensors like Kinect and Leap Motion Controller), match moving (techniques allowing insertion of computer graphics into live-action footage with correct position, scale, orientation and motion), and finally motion capturing (process of recording movements of objects or people). This review is dedicated to the question of what object recognition (motion tracking, match moving and motion capture) is and how this technique can be identified, thus synthesizing knowledge in the field. The former is further clarified, elaborated, and compared using input sensors like Kinect and Leap Motion Controller