Case Study

Automotive Photography

Improving the quality of car photography using Computer Vision

Will Perkins
Will Perkins

Business Challenge

The emergence of online automotive marketplaces has revolutionized the way consumers buy and sell pre-owned vehicles.

Quality photography is crucial for car buyers to confidently reach a decision about purchasing a pre-owned vehicle. Car sellers struggle to capture high-quality photos due to their limited knowledge of photography and lack of access to professional equipment.

“ With the help of Computer Vision, we can guide a car seller to take better photos.”


Laan Labs approached this problem for a German automaker by creating a mobile app that enables a car seller to quickly and easily photograph the exterior and interior of a car using an ordinary smartphone. With the help of Computer Vision, we can use software algorithms to guide a car seller to take better photos.

Powered by a custom-trained neural network, the app estimates the pose of a car and provides visual feedback to the user in real-time: helping to position a car in the camera's frame - to obtain the perfect shot every time.

Some of the tasks performed with Computer Vision include:

  • Car Pose Estimation

  • Sufficient Lighting Detection

  • Automatic Camera Focus

Business Value

By leveraging Machine Learning and state-of-the-art Computer Vision techniques, Laan Labs was able to quickly deliver an iOS app, with a simple & intuitive experience that produces high-quality photos with strong visual consistency.

Technologies Utilized

Computer Vision, Neural Networks, Augmented Reality, Python, iOS, TensorFlow, CoreML