Algorithmic Flesh Interaktīva instalācija — Yalin Wang

Darbs Algorithmic Flesh Interaktīva instalācija, kura autors ir Yalin Wang, ir augsti novērtēts un ļoti prestižās 2026 Bronzas balva A' Design Award ieguvējs kategorijā Ģeneratīvais, algoritmiskais, parametriskais un MI atbalstītais dizains.

BronzasĢeneratīvais· 2026

Algorithmic Flesh Interaktīva instalācija

Autors: Yalin Wang

Klients: Yalin Wang

Bronzas balva A' Design Award ieguvējs kategorijā Ģeneratīvais

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Dizains

Par Algorithmic Flesh Interaktīva instalācija

Algorithmic Flesh ir interaktīva instalācija, kas radīta kultūras mantojuma prezentēšanai. Instalācija reāllaikā izseko dalībnieka ķermeņa kustības un izmanto kustību datus kā ievadi ģeneratīvai mākslīgā intelekta sistēmai. Sistēma ir apmācīta uz Dunhuanas sienas gleznojumu attēliem un lielā projekcijā ģenerē debesu dejotāju kustībā. Kad poza sakrīt ar ierakstītu sienas gleznojuma pozu, dalībnieka siluets tiek pārveidots par dejotāju. Mērķis ir pārvērst statisku arhīvu kopīgā un dzīvā pieredzē.

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Par Bronzas balva A' Design Award

Algorithmic Flesh Interaktīva instalācija ir Bronzas balvas A' Design Award ieguvējs, ļoti prestiža atzinība, ko piešķir izciliem dizainiem, kas izceļas ar radošumu, atjautību un viedumu. Bronzas ieguvēji ir pietiekami prasmīgi un pārsteidzoši radoši darbi, kas apliecina to dizaineru plašo pieredzi, iztēli un izdarību. Sagaidāms, ka Algorithmic Flesh Interaktīva instalācija būs augsti vērtēts, apbrīnots un cienīts priekšmets, ievērojami profesionāls un inovatīvs. Šis ar Bronzas balvu apbalvotais dizains iekļauj labāko praksi mākslā, zinātnē, dizainā un tehnoloģijās un izceļas ar uzmanību detaļām. Algorithmic Flesh Interaktīva instalācija lieliski apmierina vajadzības, skar vēlmes, valdzina jūtas un piesaista zinātkāri.

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Dizainera sniegtie autori, komandas dalībnieki un tehniskie dati.

Unikālās īpašības: Algorithmic Flesh is an interactive installation redefining cultural heritage preservation as Generative Revitalization. It introduces Somatic Prompting: bypassing text interfaces, the system uses the participant's real-time physical movements as the generative seed. This somatic input drives a deeply trained AI to computationally hallucinate a dynamic, multi-limbed celestial dancer in real-time, using data from UNESCO Dunhuang murals. The audience becomes active co-creators of a living ritual.
Izmēri un iepakojums: As a digital installation, "Algorithmic Flesh" is highly scalable for gallery or museum contexts. The typical setup requires a projection area of at least 3m x 2m (supporting either 16:9 landscape or 9:16 portrait orientation, up to 4K resolution) and a participant interaction zone 3-4 meters from the screen.
Birkas: Generative AI, Embodied Interaction, Digital Ritual, Cultural Heritage, Human-AI Co-Interpretation, Somatic Prompting, Interactive Art Installation, Dunhuang Murals, Algorithmic Art, Cultural Computing, Choreography
Ražošanas tehnoloģija: Algorithmic Flesh uses a custom, closed-loop machine learning pipeline within ComfyUI. Real-time, markerless biomechanical tracking is achieved via OpenCV, MediaPipe, and YOLO26. Visual synthesis is driven by a FLUX LoRA model, fine-tuned on Tang Dynasty Dunhuang murals for absolute aesthetic fidelity. Temporal coherence is managed by Wan 2.2 Mixture-of-Experts video architecture, while the Google Veo 3 API provides cinematic spatiotemporal synthesis and native, physics-based audio generation.
Dizaina izaicinājums: The primary challenge was epistemological: How to reconstruct the dynamic, anti-gravitational flight of ancient murals in a virtual space without reducing them to lifeless 2D data? We emphasize not replacing the physical UNESCO Mogao Caves with a simulation, but speculating on new representation models. We challenge the passive museum dynamic, proposing an interactive framework where human flesh computationally hallucinates and sustains the continuous flow of a broken historical lineage.
Pētījums: This research addresses the loss of kinesthetic knowledge in static cultural heritage by introducing a Generative Revitalization framework. Pioneering somatic prompting, the project explores how a participant's body guides a generative AI without text. The machine, trained on Dunhuang mural archives, computationally generates lost transitional movements between ancient poses. This offers a new perspective on digital materiality, transforming a passive archive into an embodied, co-interpretive ritual.
Iedvesma: How can we reawaken a dance frozen in stone for a millennium? Traditional digital preservation secures visual fidelity but flat-lines the dynamic essence of the Dunhuang Apsara murals into static maps—a Crisis of Stasis. Inspired by Heimkehren (returning home) and Buddhist philosophies of Anitya (Impermanence) and Pratityasamutpada (Interdependence), the design treats machine intelligence as a collaborator, celebrating the poetic instability of forms in transition as Digital Epiphanies.
Projekta ilgums: The project was developed over a 10-month period from January to October 2025. The research and technical implementation were conducted in Beijing, China, in affiliation with the Central Academy of Fine Arts.
Darbības plūsma: A participant stands before the projection. Instantly, a "Cosmic Telemetry" UI tracks their skeletal data in real-time. As they move, the system calculates their posture against a canonical Dunhuang dataset (e.g., "raised_leg_flying [0.96] Mogao Cave 285"). Upon a high-confidence match, this somatic prompt triggers the AI. The UI dissolves, and the user's silhouette morphs into a fluid, hyper-realistic celestial dancer, transforming the viewer into a co-creator of a living ritual.
Patenti: Copyrights belong to Yalin Wang, 2025. All algorithms and visual outputs are original research generated for academic and artistic purposes at CAFA.
Attēlu autori: Image #1: Creator Yalin Wang, Algorithmic Flesh, 2025.
Image #2: Creator Yalin Wang, Algorithmic Flesh, 2025.
Image #3: Creator Yalin Wang, Algorithmic Flesh, 2025.
Image #4: Creator Yalin Wang, Algorithmic Flesh, 2025.
Image #5: Creator Yalin Wang, Algorithmic Flesh, 2025.
Video Credits: Creator Yalin Wang, Algorithmic Flesh, 2025.