THE VIDEO SHELF · signed distance field rendering
Alex Evans at Umbra Ignite 2015: Learning From Failure
Media Molecule's Alex Evans recounts the journey, including the failures, of finding the Dreams engine, based on his Siggraph 2015 talk. It covers the signed-distance-field and splat-based rendering approach and the artistic goals behind it.
Why HN readers recommended it
HN calls it an inspirational must-see on SDF rendering and a favorite tech talk for graphics programmers.
This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.
Video & recommendation details
- Creator / channel
- Media Molecule
- Topic
- signed distance field rendering
- Format
- talk
- Level
- advanced
- HN recommenders in dataset
- 7
- HN mentions in dataset
- 11
- Recommendation years in dataset
- 2017–2026
These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.
From the original HN conversations
Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.
(dev behind sculptgl, but I didn't make the HN story) Nice project! sculptgl is based on polygons (tris/quads only, and using webgl for rendering). As for the other project it was just as a quick and dirty experiments :). [LINK] [LINK] On Unity there is …
stephomi on Hacker News · 2020-10
In A 3D sculpting web applicationHg ( [LINK] ) is a great resource. I'm not a fan of the non-commercial license. The intro on the top of the site has a lot of great links to resources outside of iq, including the pouet.net thread on Raymarching, John Hart's original sphere …
Impossible on Hacker News · 2017-11
In Making WebGL Dance: How, Where, and What to Draw (2013)Alex Evan's talk on developing the renderer for Dreams: He's given several versions of this talk (including the Advancements in Real-time Rendering course at Siggraph), but here's one available online: [VIDEO]
Mr_P on Hacker News · 2018-04
In Ask HN: What is your favourite tech talk?
Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.