About HsienYu Cheng (鄭先喻)

HsienYu Cheng (鄭先喻) is a Taiwanese artist and software developer born in 1984 in Kaohsiung. He creates artworks, software, and experimental bio-electronic devices that examine human behaviour, emotion, software, and human-machine relationships. Awards include the 2014 Taipei Digital Art Award First Prize, 2017 Kaohsiung Art Award New Media Art First Prize, 2019 Tung Chung Art Award, 2021 19th Taishin Arts Award Visual Art Award, and a 2023 S+T+ARTS Nomination / Honorary Mention at ARS Electronica. Recent exhibitions include ARS Electronica 2023 and Sónar 2025 Barcelona, with further shows in the Netherlands, Slovenia, Norway, Italy, Germany, France, Austria, and Korea.

鄭先喻,1984年生於台灣高雄,藝術家兼軟體開發人員。創作藝術作品、軟體及結合電子設備的實驗性生物電子裝置。透過專注於人類行為、情感、軟體以及人機關係的作品,以幽默的方式傳達對社會與環境的獨特見解。曾獲2014年台北數位藝術獎首獎、2017年高雄獎新媒體藝術首獎、2019年銅鐘藝術獎、2021年第十九屆台新藝術獎視覺藝術獎,並於2023年獲得奧地利電子藝術節S+T+ARTS提名/榮譽獎。

  • Review & News
  • About
    • CV.
    • Contact
  • Solo Exhibitions ⬅︎
    • [.user ] - 2023
      • Info.
      • Works
    • % Consumption of Computing - 2023
    • Eyes、Ears、Nose, Tongues...those parts - 2023
      • Info.
    • Revenge Scenes - 2021
    • Injector After Null - 2020
      • Info.
      • Works
    • Assimilator - 2019
      • Info.
      • Works
    • Injector before Null - 2017
    • Secondlife: habitat - 2016
    • 1ed6318fc5481dda3ded... - 2016
    • Collector - 2014
  • Works
    • 2025
      • Traced
    • 2024
      • ThereWillBeWorks
      • Credit Make You Free
      • todayisnotwhatyoulike
    • 2023
      • Around 7 Meters is more fun
      • A slightly different browser
      • % consumption of computing
      • There is Another Capital Beneath the Waves
    • 2022
      • Happens To Be Performing
      • It Could Be You
      • Annoyanony
      • Minimal Input @ C-lab
      • don't know... what do you think?
    • 2021
      • Photo of ID
      • Revenge Scenes
      • Game of Life
      • Crystal Seeding
    • 2020
      • discharge what you charged: room edition
      • invariable variation
      • de centralize
      • We are saying what you are ruling
      • T.R.M 2.0 :Infodemic
    • 2019
      • Hijacker:{,}
      • Discharge what you charged
      • Others
    • 2016
      • Sandbox
      • Second Life: Habitat
      • Untitled: The result
    • 2015
      • Hobo
      • Artist's daily job
      • We all love F & D
      • isISis
      • The terminal is
    • 2014
      • Rc_bOAT
      • Dish on Fish
      • portrait 2014
      • MissionFail
    • 2013
      • portrait 2013
      • Afterlife ver.2.0
    • 2011
      • Afterlife
      • portrait 2011
      • heartcoke
×

Around 7 Meters is more fun

2023

joystick, display, customized software, camera and metal, machine learning algorithms

Dimension variable (minimum size: 7 meter )

“Around 7 meters is more fun”創造一個特殊的情境,藉由情境與限制,去轉變溝通方式。參與者為了理解展示的視覺效果,不僅需要仰賴觀察者的描述、描繪和表達,更需要這些來傳達意義。這種互動促進了參與者和觀察者之間更緊密的合作,彌合了所見和所未見之間的差距,重新定義了人類感知的多面性。其中也運用機器學習的方式,去限制操作參與者無法看見其自己創造的結果,而觀察者也無法運用相機紀錄其結果,這兩種規則去賦予軟體表現接近於人類的情感邏輯,藉由此方法,去製造特殊的感知與互動經驗,重新思考可見和不可見之間的關係。

Description of the project

Around 7 Meters is More Fun displays the image trajectory drawn in real time with a joystick onto a remote screen. While observers can see the images generated on a screen situated on the opposite end of a 7 meter long structure, the participants who manipulate the joystick in the other end are deprived of this vision. The resulting images also cannot be captured or recorded. Consequently, participants must rely on the descriptions or expressions of the observers to conjure an unseen scene.

The work creates a unique context that transforms communication by exploiting on-site elements and visuality constraints. In order to understand the visual effects generated, participants rely not only on the observer's descriptions, depictions, and expressions but also need these to convey meaning. This interaction triggers a closer collaboration between participants and observers, bridging the gap between the seen and the unseen and redefining the multiplicity of human perception. Machine learning tools combine with prompts, objects and motion recognition software, restricting participants from seeing the output of their own interventions, and depriving observers from using their cameras to record these results. These two rules provide the software with a closer approximation to human emotional and social logic, creating a unique experience of perception and interaction from which to rethink the relationship between the visible and the invisible.

In an environment saturated with internet information, where technology and media have significantly shortened attention spans, the way humans receive sensory stimuli has changed similarly on the informational level. Communication and comprehension are markedly different from the past. Around 7 Meters is More Fun enables observers or audiences to become witnesses, translating visual experiences into language and other non-visual forms of communication.

This work involves two distinct machine learning models and algorithms. ReID (Person Re-Identification) aims to assist in remembering who is operating the joystick. When the operator approaches the screen, the system will erase the image. The system is able to recognise the individual for a certain period of time, even after he/she has left. GroundingDino serves in detecting image/video capture devices.

Short project summary

Around 7 Meters is More Fun displays the image trajectory generated by participants manipulating a joystick onto a remote screen. Only observers can see the images that appear on the screen; neither the participants themselves can see them nor can the images be captured or recorded. Consequently, participants must rely on the descriptions or expressions of the observers to conjure an unseen scene. Here, I create a unique interactive situation that compels people to reconsider the distinctions and connections between the seen and the unseen.

Photo by Eslite gallery

 

鄭先喻個展[.user ]|2023 9/16 - 10/14|誠品畫廊 from ESLITE GALLERY on Vimeo.

Close
HsienYu Cheng | 鄭 先喻

© chenghsienyu - Attribution-NonCommercial-ShareAlike 4.0 International  (CC BY-NC-SA 4.0) 

Docs_Kit