Improving digital avatars through depth estimation

25%
boost in user engagement
40%
reduction in rendering latency
Improving digital avatars through depth estimation
Adding the depth estimation module to digital avatars for existing NFT marketplace to improve their accuracy.
Industry:

AI Startup

Location:

Germany

Technologies
Tensorflow
AWS
MediaPipe
01

About the Client

This project focuses on developing an interactive media marketplace that empowers users to create, share, and trade digital collections across multiple ecosystems. The platform integrates advanced creation tools, allowing users to design unique content effortlessly. It also features NFT (Non-Fungible Token) capabilities, enabling users to tokenize and monetize their digital assets securely.

Improving digital avatars through depth estimation
02

Challenge

The client already had a successful marketplace featuring NFTs for mobile devices, but they wanted to enhance digital avatars with greater detail and personalization. A key challenge was that the existing digital avatar system did not account for the distance between the device and an object (such as a human), which affected the avatar’s accuracy.

03

Solution we Delivered

Our primary task was to develop and integrate a missing component that would allow the platform to accurately estimate the distance between objects (e.g., a human and a camera) and improve the overall quality of digital avatars.

Depth Estimation Module

We implemented a depth estimation module using Convolutional Neural Networks (CNNs) with specialized configurations, including deep layers, optimized kernel sizes, and pooling layers. This module captured essential patterns such as the apparent size of known objects, perspective, distance, and scale, enabling accurate identification of the spatial layout and the distance between objects (e.g., a human and the camera).

Digital Avatar Accuracy Improvement

We calibrated the camera sensors to perform robust 3D rendering, significantly enhancing the accuracy and realism of digital avatars.

Integration with the Marketplace Platform

After developing the depth estimation module, we successfully integrated it into the existing platform, which was built using MediaPipe. This integration ensured that all components worked seamlessly together.

04

Client’s Results

By enhancing the AI algorithm and computer vision technology, the client significantly improved the quality of digital avatars, resulting in a better user experience. These improvements led to higher NFT sales and increased profitability for the client.

~40% improvement in avatar personalization accuracy

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