PoC Device for Wide-Range Video Recording

Merging two camera feeds in real time

The client is an insurance technology company that develops telematics solutions. This project was a dashcam-like device for installation on a vehicle windshield.

Case Highlights

Softeq created a proof-of-concept solution for real-time video stitching
  • NXP-based solution
  • Real-time video processing using synchronous exposure, white balance corrections, stitching, and squeezing algorithms
  • Covers a 200+ degree field of view
  • Wi-Fi and LTE connectivity
Project Information
Engagement model





Firmware Developers


Hardware Engineer

More Details


The client wanted Softeq to create a proof of concept (PoC) for real-time video stitching.

This system had to detect accidents, watch the driver, and call for help if required. Additionally, it needed to save high-quality videos to help with car insurance claims. If an accident happened, the system needed to send videos from an SD card to the cloud automatically.


Real-Time Video Stitching

Softeq developed a PoC solution that combines two video feeds to create a single panoramic video. Due to the apparent difference in the object position caused by different camera angles, simply merging the feeds without additional processing was not enough to create a seamless video. For this reason, we developed a Linux board support package that enables the solution to apply the necessary video corrections in real time. The solution is based on the NXP processor and supports Wi-Fi and LTE connectivity for sending data to the AWS cloud.

How it Works

1. Applies synchronous exposure and white balance corrections to video footage obtained from both cameras

2. Projects the videos on a 3D sphere

3. Merges the feeds using a smooth stitching algorithm

4. Maps the merged video on to a two-dimensional plane

5. Removes the fish-eye effect using the squeezing and stretching algorithms

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Wide range video recording with real-time processing

Softeq developed a PoC solution that helps create panoramic videos by merging two camera feeds in real time. The solution is able to cover a field of view of more than 200 degrees. 

Currently, we are working on an MVP version of the driver assistance solution, which will also support Alexa. Next, we will develop a geofencing function that notifies drivers when they enter an unsafe area.

Our solution could serve as a basis providing data needed for further analysis should the client decide to create an ADAS system that helps drivers avoid on-road collisions.