Video annotation and computer vision data labeling
Contributed to video annotation projects on Atlas Capture, supporting the development of computer vision models. The scope of the project involved labeling and analyzing large volumes of video data to identify objects, actions, and scene elements across multiple frames. Performed tasks such as bounding box annotation, object tracking, and classification, ensuring accurate frame-by-frame labeling in accordance with detailed project guidelines. The project required handling high data volumes while maintaining consistency and efficiency. Adhered strictly to quality assurance standards by reviewing annotations, correcting inconsistencies, and meeting accuracy benchmarks set by the platform. Maintained high attention to detail, followed evolving instructions, and consistently delivered reliable, high-quality labeled data for AI training purposes.