4 Top Computer Vision Startups In Automotive Out Of 250

Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups in the automotive industry. As there is a large number of startups working on a wide variety of solutions, we decided to share our insights with you. So, let’s take a look at promising computer vision solutions for the automotive sector.

Heat Map: 4 Top Computer Vision Startups

For our 4 picks of computer vision startups, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 4 interesting examples out of 250 relevant solutions. Depending on your specific needs, your top picks might look entirely different.

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PickIt – Vision-Guided Robot (VGR)

One of the reasons computer vision impacts car manufacturing is that it provides flexibility in robotic systems. Industrial robots are lacking vision, so they are only capable of performing the same task repeatedly. Vision-Guided Robots (VGR), on the other hand, can perform more complex tasks, such as loading and unloading pallets, picking and placing objects, or even handling products individually. Belgian startup Pickit develops a 3D camera & picking software which can be attached to robots thus transforming them into VGRs.

Scandit – Wearables

Embedding computer vision algorithms into wearables enables hands-free object recognition and scanning which are potential applications for quality control and maintenance in car manufacturing. Startup Scandit offers a software solution for smart devices combining computer vision and augmented reality technologies. This way, wearable devices, such as smart glasses, become hands-free barcode scanners and object recognition tools.

Dreyev – Driver Monitoring

As we saw in our previous article on driver monitoring systems, incorporating sophisticated computer vision algorithms is highly reliable. They monitor driver’s movements – from various body positions to the smallest facial movement, such as mimicry, to detect a lack of attention and fatigue. Dreyev’s digital assistant solution uses computer vision to analyze head poses and eye-movements to alert the driver when a distraction occurs.

DeepScale – Perception & Localization

In addition to monitoring the driver’s and passenger’s behavior, computer vision technologies also detect the environment around the car, allowing vehicles to better interact with each other and smart elements of the infrastructure. What is more, computer vision algorithms help to classify, annotate and provide better image understanding when it comes to the perception and localization of an autonomous vehicle. US-based startup DeepScale develops a software solution for Advanced Driver-Assistance Systems (ADAS) and autonomous vehicles, enabling them to integrate individual modules (“AI blocks”) to scale various perception needs.

What About The Other 246 Solutions?

While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence for your Proof of Concept (PoC), partnership, or investment targets. The 4 computer vision startups showcased above are promising examples out of 250 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.