US-DATAData Annotation
Cabinet
Motion tracking teaches neural networks to follow objects in video streams and preserve their identity throughout the entire sequence.
Calculate project cost
Object tracking continuously follows one or more objects across frames while preserving a unique Track ID through motion, rotation, occlusion and reappearance.
Follow the position of one selected object.
Track multiple objects simultaneously with distinct IDs.
Restore identity after an object exits the frame or changes cameras.
Analyze direction, speed, stops and turns.
Annotators localize objects on frames, assign and preserve Track IDs, add classes and attributes, handle occlusion and lost visibility, mark entries and exits, and validate trajectory continuity.
US-DATA labels single and multiple tracks, dense dynamic scenes, fast-moving and partially hidden objects. We tailor tracking rules, annotation frequency and export formats to your ML pipeline.
Inconsistent labels reduce accuracy, introduce bias and can make production behavior unreliable.
We create task-specific guidelines and validate every stage so the dataset matches the model architecture and business objective.
Examples of data annotation for machine learning
Full data preparation cycle from raw data to model-ready output
How does US-DATA deliver the results business needs?
We pay close attention to quality. Even the most accurate model will not perform well if the data is labeled with errors.
Our team works under a unified annotation rule system based on multi-level review and consistency control. Every process is adapted to client needs and the specifics of the ML model. The result is a clean dataset ready for training without additional rework.
We understand how data quality affects model training.
Annotation tailored to architecture and project goals.
From pilots to large-scale data volumes.
Control at every stage and transparent metrics.
We handle non-standard and challenging scenarios.
Data exported in the format you need.
Faster model training
Higher accuracy and robustness
Lower retraining costs
Production-ready datasets
Data security and compliance
Expandable sections with indicative cost tables.
Choose parameters and get instant estimate
* This estimate is not a public offer. Final cost is determined after technical analysis and data review.
Latest materials on data annotation and machine learning
Leave a request — we will assess the task and propose the right annotation approach and delivery format.
Object motion tracking detects objects across frames, preserves Track IDs and analyzes movement. US-DATA prepares datasets for single-object tracking, multi-object tracking, re-identification and behavior analysis.
We develop annotation guidelines, run pilot labeling and multi-level quality control, then deliver a consistent dataset in the format required by your ML pipeline.
The result is data that is ready to train, validate and deploy machine learning models in real operating conditions.
