Driving All Weather Conditions Made Safe With Algolux’s Robust AI Perception Software

All Too Human

Every driver has experienced bad conditions on the road at one time or other in fog, snow or rain. Whatever the weather and state of the road and your perception of it, we’ve all struggled with seeing the bigger picture, for — in the words of the 19th-century German philosopher Friedrich Nietzsche — we’re “Human, All Too Human”.

Though our vision is a great evolutionary piece of toolkit, it’s not perfect. To augment it, we need something reliable — and that something comes in the form of AI vision systems, and in particular, a system developed by an industry-recognized team of researchers led by one Felix Heide.

This symbiosis is the startup Algolux, a computer vision startup based in Montreal, Canada. Founded in 2015 by Heide, along with Jonathan Assouline and Patrick Arbez, Algolux’s Eos is an award-winning embedded perception solution platform — designed for all conditions and seasons — and the best-in-class perception technology around.


The Eos Embedded Perception Software employs efficient end-to-end deep learning architecture that can be quickly personalized to any camera lens/sensor configuration or for multi-sensor fusion. Combined with stereo or depth-sensing cameras, Eos offers an alternative to Lidar at a fraction of the cost.

Capable of detecting a driver’s surroundings in numerous conditions such as dark night, low light, glaring from dirty windshields, and snowfall etc, it also does a fine job at wide-angle pedestrian and object detection.

The technology is based on:

• Camera-Based Perception

Eos addresses individual NCAP requirements, L2+ ADAS, higher levels of autonomy from highway autopilot and autonomous valet (self-parking) to L4 autonomous vehicles as well as Smart City applications such as video security and fleet management

• Multi-Sensor Fusion

Eos provides multi-sensor early fusion for L2+ and higher autonomous vehicles and robots. Combined with stereo or depth-sensing cameras, Eos provides an alternative to Lidar at a fraction of the cost

• End-to-End Perception

Perception software enabling end-to-end learning of computer vision systems. The approach allows customers to easily adapt their existing datasets to new system requirements, enabling reuse and reducing effort and cost vs. existing training methodologies

The Eos computer vision and image optimization solutions address the mission-critical issue of safety for ADAS, autonomous vehicles, fleets, autonomous mobile robots, and smart city traffic video analytics.

The seed of the Eos came from the work of Felix Heide, Algolux’s Co-Founder and CTO. Heide earned his Ph.D. from the University of British Columbia, studying computational imaging with Professor Wolfgang Heidrich, and concluded his postdoc research at Stanford University, working with Gordon Wetzstein. Additionally, Heide is a professor at Princeton University.

Most of his research work lies at the intersection of computer vision, optimization, ML, optics, and physics.

Heide is the recipient of the AutoSens 2020 Young Engineer of the Year Award, Sensors Expo 2018 Rising Star award, ACM SIGGRAPH 2017 Doctoral Dissertation Award, and the Alain Fournier 2016 Award for Best Doctoral Dissertation in Computer Graphics.

A technology entrepreneur with 15 years of experience, Jonathan Assouline is another Co-Founder at Algolux who was Head of New Technology Initiatives/Software Manager from 2013 to 2017.

Patrick Arbenz is Algolux’s third Co-Founder. From 2013 to 2019 he acted as the startup’s Software Architect and Technology Leader who is currently a Senior Team Leader at AIRY3D, a Montreal-based 3D-vision startup.

Named to the 2021 CB Insights AI 100 list of most innovative AI companies in the world, Algolux has raised a total of $31.8 million in funding over six rounds. This VC money will help its full-stack software solution for autonomous vehicles reach its potential and keep us safe on the roads.

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