Case study

Computer vision annotation project

Image and video labeling for object detection, segmentation and tracking AI programs.

Client challenge

Needed labeled image and video assets at scale for object detection, segmentation and tracking models with a defined taxonomy.

Data requirements

Bounding boxes, polygons, keypoints and segmentation masks, annotation guidelines, acceptance thresholds and delivery schema.

Our approach

Schema and guideline calibration, pilot batch on hardest edge cases, production annotation, multi-level QA and secure delivery.

Data modality

Image and video, 2D bounding box, polygon, polyline, keypoint and segmentation masks.

Quality process and outcome

Annotator

Applies labels per project taxonomy and attribute rules.

Reviewer

Checks consistency, boundary accuracy and guideline compliance on sampled batches.

Senior QA

Edge-case review and final validation against acceptance thresholds.

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