Player Ntchito Yaikulu ya Kanema Wapa Intaneti by Suryun Hyeon

Player Ntchito Yaikulu ya Kanema Wapa Intaneti by Suryun Hyeon is a highly esteemed winner of the very prestigious 2025 Mphoto ya Bronze ya A' Design Award in Mapangidwe a Mawonekedwe, Kulumikizana ndi Zokumana ndi Ogwiritsa Ntchito Competition Category.

BronzeMawonekedwe· 2025

Player Ntchito Yaikulu ya Kanema Wapa Intaneti

by Suryun Hyeon

Mphoto ya Bronze ya A' Design Award Winner in Mawonekedwe Category

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Verified Award Winner
Verify Award Status for #167229

View at A' Design Award Press Release Award Badge

Colors

The Design

About Player Ntchito Yaikulu ya Kanema Wapa Intaneti

Malemba a Bukhu: Player ndi mawonekedwe a nsanja ya makanema omwe amalola omvera kutenga nawo mbali mu "extended reality". Makanema oikidwa pa Player amaphatikizapo kutsata mayendedwe ndi mawu, ndipo mayendedwe olembedwawo amasandulika kukhala data ya mayendedwe a 3D. Ogwiritsa ntchito amatha kutsatira zochita za kanema molondola, kenako kujambula, kusintha, ndi kugawana mtundu wawo. Chida cha Generative AI chimalola ogwiritsa ntchito kupanga ma avatar ndi maziko a kumbuyo, kotero kutenga nawo mbali n'kotheka popanda kuwonetsa nkhope kapena thupi. Mawonekedwewa adapangidwa kuti agwiritsidwe ntchito ndi zida za "extended reality" zovala pamutu, ndipo amagwirizana bwino ndi zochitika monga kuvina ndi ntchito zomanga.

The Recognition

About the Mphoto ya Bronze ya A' Design Award

Player Ntchito Yaikulu ya Kanema Wapa Intaneti ndi mmodzi mwa opambana a Mphoto ya Bronze ya A' Design Award, kuzindikirika kolemekezeka kwambiri komwe kumaperekedwa kwa mapangidwe abwino kwambiri omwe amaonekera ndi luso lolenga, kuchenjera ndi nzeru zakuthwa. Opambana a Bronze ndi zinthu zaluso kwambiri ndi zolenga modabwitsa zomwe zimatsimikizira zochitika zazikulu, kulingalira ndi kuchenjera kwa opanga awo. Player Ntchito Yaikulu ya Kanema Wapa Intaneti akuyembekezeka kukhala chinthu choyamikiridwa, chosirira ndi chokondedwa, chaukatswiri wapadera ndi chatsopano. Mapangidwe opambana Mphoto ya Bronze ya A' Design Award awa amaphatikiza machitidwe abwino kwambiri a luso, sayansi, kapangidwe ndi ukadaulo ndipo ndi abwino kwambiri chifukwa cha kusamala kwawo zazing'ono. Player Ntchito Yaikulu ya Kanema Wapa Intaneti amakwaniritsa zosowa mokongola, kukhudza zilakolako, kukopa mitima ndi kudzutsa chidwi.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: 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.
Dimensions & Packaging: 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.
Tags: XR, AR, Video Platform, UI, Interaction, Participant, Play
Production Technology: 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.
Design Challenge: 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.
Research: 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.
Inspiration: 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.
Project Duration: This project commenced in January 2024 in South Korea and was completed in April 2024 in South Korea.
Operation Flow: 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.