Multi-person Spatial Interaction in a Large Immersive Display Using Smartphones as Touchpads

Sharma, Gyanendra; Radke, Richard J.

doi:10.1007/978-3-030-55190-2_22

Cited by 3 publications

(1 citation statement)

References 35 publications

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“…The latest research focuses on newly trending technologies such as augmented reality (AR), which is also employed in the exact same scenario our solution is concerned with (wall-displayed application including remote device-based collaboration) [17]. Another study combined smartphones, Bluetooth microphones, and Kinect sensors for large screen interaction [18], while Huang et al [19] developed a huge 60-screen display for data visualization and developed an interaction framework with gestures for it. Applications such as these would greatly benefit from the proposed solution in terms of automatized communication and out-of-the-box device-application adaptation.…”

Section: Related Workmentioning

confidence: 99%

Smartphone-Enabled Interaction on Large Displays—A Web-Technology-Based Approach

Smolić,

Boras,

Horvat

et al. 2024

Electronics

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This paper proposes the design and implementation of a system for simultaneous communication of several users over a single display, such as large public displays or video walls. Motivated by the lack of software frameworks that are both free and suited for the desired level of complexity, we present a novel, out-of-the-box solution for collaborative and remotely controlled application use. The solution is based exclusively on web technologies, thus significantly facilitating usability and reach, and eliminating the need for additional software installations or the use of additional devices. The architecture of the developed solution is modular and comprises three main components: (1) the environment, (2) the remote controllable application (RCA), and (3) the controller. The environment serves as a central hub that manages the data flow and ensures synchronization between the user devices. The RCA, which runs on the large display, serves as the interface for interacting with the content, while the controller, which is loaded on the users’ smartphones, enables control and interaction with the RCA in real time. By using web sockets and a server–client architecture, the system supports device- and platform-independent remote control and centralized collaboration through an off-the-shelf communication framework entirely flexible regarding client application. In order to demonstrate the possibilities of the proposed system, several different scenarios were covered, and solutions were implemented and tested on a large display in the faculty lobby.

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Section: Related Workmentioning

confidence: 99%

Smartphone-Enabled Interaction on Large Displays—A Web-Technology-Based Approach

Smolić,

Boras,

Horvat

et al. 2024

Electronics

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An Intelligent Analytics for People Detection Using Deep Learning

Isiaka

2024

Preprint

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People detection has become crucial in various applications, from security systems and surveillance to retail analytics and traffic management. With the advent of deep learning, particularly convolutional neural networks (CNNs), we’ve witnessed significant advancements in object detection accuracy and efficiency. This paper explores the power of intelligent analytics driven by deep learning for people detection, highlighting its benefits, challenges, and potential applications. The main aim is to build a people behaviour detection framework through body language, events, objects around people and their postures to determine the behaviour of people and environment genuinely based on given attributes like walking (still or moving), sitting (still or fidgeting), running (steady paise or high speed) and standing (still or fidgeting). These attributes contribute to detecting people’s behaviour from a given input of video sequence, both in real-time or pre-recorded from MATLAB using three different deep learning algorithms (CNN, You Only Look Once (YOLO) and Faster region CNN). The results obtained were compared to determine which model best suits people’s behaviour detection.

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Research on Human-Computer Interaction Technology of Large-Scale High-Resolution Display Wall System

et al. 2023

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As an effective solution for data visualization and analysis, the large-scale high-resolution display wall system has been widely used in various scientific research fields. On the basis of investigating existing system cases and research results, this paper introduces the SHU-VAS system (60 screens, 120 megapixels) for data visualization and analysis. In order to improve the efficiency of human-computer interaction in large-scale high-definition display wall systems, we propose an interaction framework based on gesture and double-precision pointing technology. During the interaction process, an adaptive mode switching method based on user action features is used to switch between rough and precise control modes. In the evaluation experiments, we analyzed the characteristics of different interaction methods in movement and navigation interaction tasks, and verified the effectiveness of the gesture-based interaction framework proposed in this paper.

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Multi-person Spatial Interaction in a Large Immersive Display Using Smartphones as Touchpads

Cited by 3 publications

References 35 publications

Smartphone-Enabled Interaction on Large Displays—A Web-Technology-Based Approach

Smartphone-Enabled Interaction on Large Displays—A Web-Technology-Based Approach

An Intelligent Analytics for People Detection Using Deep Learning

Research on Human-Computer Interaction Technology of Large-Scale High-Resolution Display Wall System

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