View Case Study
Player tracking and recognition using alternative technologies for facial recognition

Utilize computer vision to recognize players from different sports without using facial/biometric information for GDPR compliance.

01

GDPR Compliant Tagging for Sports


Generate time-coded sequence-based metadata around players, kits and objects without using facial information.

02

Accelerate Content Repackaging

Accelerates the creation of highlights/recommendations through AI-driven workflows

03

Monetise Archives Better

Increase creation possibilities for new media products and personalised content by getting access to what is hidden or unseen

AI Workflows

Enabling deeper search capabilities of important players in sports archives without using facial or personal data.

01

AthenasOwl GDPR Compliant Player Recognition Service

Detection and tracking of players without using facial embeddings but by different sports identifiers, objects and kits on-scene level.

Explore the Technology Features
GDPR compliant metadata. Time-coded sequence-based metadata around players, kits and objects without using facial information.

Handle motion blur

Handle motion blur and occlusion while generating granular metadata

Event Recognition

Automated Event Recognition and Classification of the localized highlight-worthy moments

Club/Sponsor Logo Detection

Automated detection of the club, and sponsor logos within a match.

Logo Detection

Automated detection of sponsor logos to analyze digital exposure of brands

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