Facial Recognition Jobs

We are looking for participants living in Italy, Spain, Poland, Romania, South Africa, Argentina, Brazil, Netherlands, Greece, Croatia, Philippines, India, and Mexico for a simple data collection task. The task involves recording short videos and taking photos of your face while performing specific facial movements and gestures. This is a self-guided task that you can complete at home. The recordings will include: Normal face (no obstruction) Face partially covered with items such as glasses, masks, head coverings, or makeup that changes facial appearance Before starting, you will complete a short survey to confirm eligibility and basic details. Based on your answers, you will receive the instructions for your task. Task Details Record 15–20 second videos or take images of y...

I already run a React Native gym-management app on Android that uses in-app facial recognition for member check-ins, access control, and attendance logs. The codebase is stable; I simply need the same experience replicated on iOS—no new features, no redesigns, just a faithful port. Here is what I expect: • Compile and configure the existing React Native project for iOS, resolving any platform-specific dependencies (camera permissions, Face ID hooks, push notifications, etc.). • Confirm that facial recognition flows work identically to the Android build and meet Apple’s privacy guidelines. • Produce an archive build ready for TestFlight and a signed App Store submission package. • Provide brief setup notes so I can reproduce the build locally (Xcode version,...

I need an end-to-end system that automatically counts every passenger who enters or exits a bus and, at the same time, lets only authorised riders board through face recognition. The headcount must update live and stream to my security team’s server so they can monitor occupancy and verify that no unauthorised person is on board at any moment. Here is what matters to me: the facial verification must be fast enough to avoid boarding queues, the counting accuracy should stay above 98 %, and the data flow has to be truly real-time, not batch. If you already work with edge cameras or depth-sensing devices for people counting, please tell me how you will integrate them with your face-recognition engine and how you plan to push the feed straight to our internal server (REST API, MQTT, or ...