Another machine learning experiment from Samim explores regression method to moving image, breaking down each frame into visual compartments creating a polygon / Modernist style:
Regression is a widely applied technique in machine learning … Regression analysis is a statistical process for estimating the relationships among variables. Lets have some fun with it ;-)
… This experiment test a regression based approach for video stylisation. The following video was generated using Stylize by Alec Radford. Alec extends Andrej’s implementation and uses a fast Random Forest Regressor. The source video is a short by JacksGap.
You can find out more about the machine learning experiment here
Noodle tearing up the dance floor
Hands-On Python & Xcode Image Processing: Build Games & Apps ☞ http://go.learn4startup.com/H1iINoD7z
#DeepLearning
Portal in AR looks amaaaazing!
Unfortunately this is just a demo on HoloLens by developer KennyW, but here’s hoping it comes to life one day.
Machine gun position on the German R-class Zeppelin ‘LZ 63’, 1916-17
via reddit
Video game created by @slow-bros is an adventure whose assets were originally handmade to produce a stop-motion feel to the experience:
Harold Halibut is a modern adventure game, with a strong focus on storytelling and exploration. Set in a spaceship, stuck under sea on a distant water planet, you slip into the tiny shoes of Harold. As a young janitor and lab assistant to Professor Jeanne Mareaux, one of the lead scientists on board, he tries to help out in her attempt to find a way to relaunch the ship.
All that can be seen in the game is carefully built in a real-world workshop using classic sculpting, set building and clay and puppet fabrication techniques. We’re not even buying supplemental model train trees or anything.
Our love of stop-motion films, childhood nostalgia and respect for traditional craftsmanship are some reasons for this. Patience and taking a break from an ultra-fast paced digital reality are big factors as well.
The project has just released a kickstarter campaign which has more information, which you can find here
Apple have just published an example for developers on how to use their front facing camera on the iPhone X for AR apps:
This sample app presents a simple interface allowing you to choose between four augmented reality (AR) visualizations on devices with a TrueDepth front-facing camera (see iOS Device Compatibility Reference).
The camera view alone, without any AR content.
The face mesh provided by ARKit, with automatic estimation of the real-world directional lighting environment.
Virtual 3D content that appears to attach to (and be obscured by parts of) the user’s real face.
A simple robot character whose facial expression is animated to match that of the user.
Link
An intro video can be found here
TESS_ERACT
HV. Self-replicating artificial intelligence program named Dorothy.
Galerians: Ash (2002) PS2
Project from Universal Everything is a series of films exploring human-machine collaboration, here presenting performative dance with human and abstracted forms:
Hype Cycle is a series of futurist films exploring human-machine collaboration through performance and emerging technologies.
Machine Learning is the second set of films in the Hype Cycle series. It builds on the studio’s past experiments with motion studies, and asks: when will machines achieve human agility?
Set in a spacious, well-worn dance studio, a dancer teaches a series of robots how to move. As the robots’ abilities develop from shaky mimicry to composed mastery, a physical dialogue emerges between man and machine – mimicking, balancing, challenging, competing, outmanoeuvring.
Can the robot keep up with the dancer? At what point does the robot outperform the dancer? Would a robot ever perform just for pleasure? Does giving a machine a name give it a soul?
These human-machine interactions from Universal Everything are inspired by the Hype Cycle trend graphs produced by Gartner Research, a valiant attempt to predict future expectations and disillusionments as new technologies come to market.
More Here