Advances in Mobile Computing and Multimedia Intelligence
Description
This book constitutes the refereed proceedings of the 23rd International Conference on Advances in Mobile Computing and Multimedia Intelligence, MoMM 2025, held in Matsue, Japan, during December 8-10, 2025.
The 10 full papers and 6 short papers included in this book were carefully reviewed and selected from 31 submissions. They were organized in topical sections as follows: Mobile and Wearable Systems; Security and Trust in Mobile Environments; and Immersive and Context-Aware Computing.
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Content
.- Mobile and Wearable Systems.
.- Diffusion-TS: A Hybrid Model for Human Skeleton Prediction.
.- LightVideoRAG: Low-Resource Long Video Question-Answering via Adaptive Sampling and Context-Aware Retrieval.
.- Exploring the Design of Context-Aware Widget Recommender System in Mixed Reality.
.- System to Support Acquiring Midfoot Strike Running through Intermittent Feedback of Foot Pressure Balance.
.- Ear Canal Pressure-Based Oral Gesture Recognition for Saxophone Performance.
.- Step-based Sensor Data Segmentation using Foot Pressure Sensors.
.- Security and Trust in Mobile Environments.
.- Anti-ESIA: Analyzing and Mitigating Impacts of Electromagnetic Signal Injection Attacks on Image Sensing.
.- User-to-PC Authentication Through Confirmation on Mobile Devices: On Usability and Performance.
.- Silent Speech Recognition Using Ear Canal Pressure Changes.
.- Dependency-Based Evolution Planning of a Multi-Version Microservice RAN Application.
.- Immersive and Context-Aware Computing.
.- Napping in the Virtual World: Exploring the Effects of VR Audiovisual Relaxation on Napping.
.- A Method for Reducing Cognitive Load by Virtually Relocating the Visual Position of Distracting Sound Sources Away from the Task Direction.
.- AR Superimposed Display System with Video Synchronization.
.- Grounded in the Fields: Participatory Foundations for Human-Centered Agricultural Software in Central Borneo.
.- Human-in-the-Loop Generative AI for Explainable Insurance Decision Support.
.- Lyric-Aware DJ Track Recommendation based on Semantic Relationships.
