The Overview

Miro Al is an award-winning sports analytics Al startup which analyzes millions of bodies and faces across team sports and race events across the globe. Their Al within seconds identifies all legible jersey/bib numbers, player faces, and branded gear information in real time from photos/video captured by photographers. Sporting events include marathons, team sports like football, soccer, ice hockey and basketball.

The Challenge

Miro's training data compiles of up to 30,000 images per event from solo & team sport games. For Miro to have a high confidence model, data is required to be tagged on the go in a global time zone. Tagging consists of athlete faces, jersey numbers and other gear items, that need annotation on the fly at times to optimize Algorithm results.This challenge required Miro to have a team which understood the game in question, sporting teams, grasp of players participating and a robust communication around the clock. It also required extensive annotation of 100% area in every image including tiniest of details via segmentation annotation.

The Solution

To cope up with the challenge, AISmartz was first put to test with other workforce partners in a two-week assignment. AISmartz Team strategized with a fast-paced learning curve for business rules and player identification with a careful shortlisting of team for the task. Annotators were trained by educating them with sport videos, player roasters and memory tests. AISmartz eased resource budget and operational hassle for Miro's core team by tagging up to 800 images per shift along with bibs cleaning of 2,000-3,000 images per hour in case of marathon events.With flexible hours that matched to client's team, AISmartz optimized work in shifts. The team today identifies players and matches them to teams natively in real time. Annotators even update Miro's database for player transfers and retirement every Monday by looking up Sporting

The Results

In addition to their bread & butter market of marathons, Miro can confidently rely on Al Smartz while they cover diverse team sports such as NBA, Major League Soccer, NFL, Indian Premier League, and Ice Hockey League. All with speed, accuracy, time zone and cost efficiency, without fretting about having an expensive onshore annotation team.
At AIsmartz, we understand that data from different clients of yours could have varied labeling requirements. We take a nuanced approach while our workforce works on your data.

Drop us a line to know how you can achieve seamless data labeling.

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