由設計師 Suryun Hyeon 創作嘅 Player 影片平台介面係備受推崇嘅 2025 A' Design Award 銅獎得獎作品，獲獎類別為介面、互動及用戶體驗設計。

銅介面· 2025

Player 影片平台介面

由 Suryun Hyeon

介面類別嘅 A' Design Award 銅獎得獎者

27,448

經驗證嘅獲獎者

驗證設計 #167229 嘅獲獎狀態

喺 A' Design Award 查看新聞稿獎項徽章

色彩

設計

關於 Player 影片平台介面

Player係一個支援延展實境(XR)受眾參與嘅影片平台介面。上傳到Player嘅影片包含動作同聲音追蹤功能，錄製嘅動作會被轉換成3D動作數據。用戶可以準確跟隨影片入面嘅動作，然後錄製、編輯同分享屬於自己嘅版本。一個生成式AI工具俾用戶創建虛擬形象同背景，令到用戶唔使露面或露出身體都可以參與其中。呢個介面係專為頭戴式延展實境裝置而設計，適合舞蹈同建構類任務等活動使用。

榮譽認可

關於A' Design Award 銅獎

Player 影片平台介面是 A' Design Award 銅獎得主，這是授予以創造力、獨創性和敏銳見長的傑出設計的極具聲望的認可。銅獎得主是技藝嫻熟、創意驚人的作品，印證了其設計師豐富的經驗、想像力與機智。預計Player 影片平台介面將成為一件備受推崇、令人欽佩且被珍愛的物品，兼具顯著的專業性與創新性。這件贏得 A' Design Award 銅獎的設計融入藝術、科學、設計和技術領域的最佳實踐，並因注重細節而出類拔萃。Player 影片平台介面出色地滿足需求，觸動渴望，迷住情感，並吸引好奇心。

設計背後

新聞資料包

由設計師提供嘅製作人員名單、團隊成員同技術詳情。

獨特屬性: Player redefines video content by enabling audience participation in XR. While traditional platforms limit interaction to "likes" or "comments," Player turns viewers into active participants. It allows users to explore 3D motion data, follow along, and share their actions. With generative AI, users can create avatars and backgrounds, making participation accessible to all. This transforms video enjoyment into an immersive, multidimensional experience.
尺寸同包裝: This project focuses on an AR user experience within XR and is designed to be compatible with HUD-type devices. It is expected to function seamlessly on devices like Meta's Quest or Apple's Vision Pro. However, AR glasses in the form of smart glasses may currently face challenges in achieving full technical implementation.
標籤: XR, AR, Video Platform, UI, Interaction, Participant, Play
生產技術: Videos uploaded to Player include motion and sound tracking. Whether recorded with XR devices or standard cameras, movements within the video are converted into 3D motion data to facilitate easy participation. Additionally, a generative AI-powered UI allows users to create avatars and environments, enabling them to join videos in their desired appearance. This combination of technologies ensures an accessible and personalized experience for all participants.
設計挑戰: The main challenge during the project was developing a method to extract 3D motion data and effectively visualize it. Seeking advice from experts, I learned that motion tracking was feasible and adopted active use of 3D tools, which ultimately allowed for effective representation.
研究: Type of Research: Exploring user video participation possibilities through 3D motion tracking and generative AI in XR environments.
Research Objective: To explore dynamic possibilities where users transform into active participants through modern technological integration.
Methodology: Project functions derived from in-depth user interviews and insight clustering.
Data Collection and Research Tools: Insights gathered through one-on-one in-depth interviews and collective opinions collected via online surveys.
Participants or Experiments: Conducted primarily with Gen-Z users in their teens and twenties.
Results: Most participants acknowledged the increasing trend of video participation but agreed on the limitations of current video platform features. They expressed that generative AI, enabling changes in appearance or environment, would make video participation more engaging and enjoyable. There was also significant demand for customizable avatar and filter features.
Insights and Impacts: Current video platforms, despite their dynamic content and user expectations, offer only limited functionality, rendering video consumption a static activity. Integrating XR features and generative AI could encourage more active participation from viewers.
Business Impacts: Both participants and creators are likely to spend more time on the platform, increasing app engagement and session duration, which would naturally lead to higher ad revenue and other supplementary income. This would improve video quality and user reactions, creating a positive feedback loop.
Real-Life Phenomena: Viewers will no longer consume videos passively through static comments. Instead, they will enjoy watching participation videos that capture how others laugh, cry, or act, making video consumption a more dynamic and engaging experience.
靈感: As someone who enjoys video content and wants to join challenges, I often felt burdened by the need to edit videos and hesitant to show my face or body. Following complex actions in videos also proved challenging. To address these struggles and explore new possibilities for enjoyment, I aimed to use generative AI in XR to create a solution. I look forward to a day when everyone, regardless of age or background, can enjoy videos in their own way, with the appearance and actions they choose.
項目時長: This project commenced in January 2024 in South Korea and was completed in April 2024 in South Korea.
操作流程: Users who find a video they want to participate in first set up their desired environment. After customizing their avatar and selecting a background, they can start recording. Utilizing 3D data provided by the video, users can accurately follow actions, including details that are usually hard to notice. This can be applied to dancing, building LEGO, reaction videos, and more. Once recording is complete, users can easily edit their participation and share their experience with others.