High-volume landmark annotation — 10+ years’ experience, 540+ annotators, 38M+ images; ISO, HIPAA & GDPR-aligned for enterprise teams
Landmark annotation supplies exact coordinates for key points and reference markers in images and video. These labels support object localization, spatial alignment, and 3D reconstruction—capabilities used in autonomous navigation, facial and hand analysis, AR, sports analytics, and imaging. Quality landmarks reduce model errors, strengthen spatial understanding, and speed deployment.
Precise BPO India combines 10+ years of experience with 540+ annotators to deliver scalable landmark datasets. Our workflows fit SBU, MBU, and enterprise needs: we define taxonomies, point structures, and labeling rules so each coordinate matches client and model requirements.
We have processed 810M+ images, including 38M+ landmark tasks across automotive, healthcare, retail, agriculture, geospatial, sports, robotics, and industrial AI. This scale helps clients train large models, manage lifecycles, and iterate consistently across versions. Security and quality are core.
We implement ISO 27001 controls and follow GDPR- and HIPAA-aligned practices where needed. Multi-stage QC—automated checks, reviewer audits, and sampling—maintains accuracy for high-volume datasets and specialized workflows.
Serving the US, UK, EU, ME, APAC, LATAM and global markets, Precise BPO India provides India-based, cost-efficient landmark annotation that improves spatial accuracy and accelerates production AI. From face and hand landmarking for gesture and expression analysis to sports action landmarks, AR point mapping, and 3D reference markers, we deliver consistent, model-ready datasets.
Multi-point landmarking – Label multiple reference points in crowded or overlapping scenes.
Precise coordinate tracing – Capture accurate coordinates to support object alignment and mapping.
Occlusion-aware detection – Identify partially hidden landmarks to improve model resilience.
Dense landmark mapping – Handle images with many key points in complex environments.
3D & depth-aware labeling – Support multi-dimensional landmarks for AR/VR and spatial AI.
Instance & semantic landmarking – Annotate both individual objects and class-level reference points.
Custom taxonomy & ontology setup – Flexible annotation structure tailored to client needs.
Scalable enterprise workflows – Efficiently manage SBU, MBU, and enterprise-level volumes.
Requirement Understanding
Define project goals, landmark types, labeling rules, and point-placement standards with clients.
Data Collection & Setup
Curate, clean, and prepare images/videos for high-quality annotation inputs.
Data Labeling
Annotators add key points, coordinates, and reference markers based on client rules.
Quality Check
Multi-layer QC combining automated checks and human review ensures accuracy.
Client Review
Incorporate client feedback, refine landmark rules, and adjust workflow.
Final Delivery & Support
Deliver datasets in requested formats and provide scalable support for enterprise AI pipelines.
Client Need:
Accurate road, lane, and vehicle reference points for ADAS.
Solution:
High-quality landmark coordinates with multi-layer QC.
Result:
Model accuracy improved 22%, reducing navigation errors.
Client Need:
Anatomical landmarks for surgical planning and diagnostic AI.
Solution:
HIPAA-aligned landmark annotation with precise coordinates.
Result:
Detection sensitivity increased 18%, improving patient outcomes.
Client Need:
Facial keypoints and hand landmarks for gesture, gaze, and expression analysis.
Solution:
Dense multi-point face and hand landmarking with occlusion handling and temporal consistency.
Result:
Recognition models achieved higher precision with fewer false positives.
Client Need:
Player movement and action tracking for analytics and highlight generation.
Solution:
Joint, limb, and motion landmarking with frame-to-frame tracking.
Result:
Player-action models delivered improved recall and better event detection.
Client Need:
Mechanical parts and assembly line positioning for automation.
Solution:
Dense landmarking for occluded and overlapping components.
Result:
Pick-and-place accuracy improved 30%, reducing defects.
✔ 10+ years of landmark annotation experience supporting AI pipelines globally.
✔ 540+ skilled annotators delivering high-volume, precise datasets efficiently.
✔ Proven experience with SBU, MBU, and enterprise-level projects. 38M+ images processed with high-accuracy landmarking.
✔ ISO, HIPAA, and GDPR-aligned workflows ensuring secure, compliant handling.
✔ Indian-based, high-volume, low-cost solutions for global AI teams.
✔ Flexible taxonomy, multi-class labeling, instance, and hierarchical point-setup support.
✔ Multi-stage QC combining human and automated verification guarantees consistent datasets.
✔ Dedicated client support and ongoing workflow optimization for enterprise projects.
✔ Scalable solutions for urgent or large-volume landmark annotation projects.
It marks key points, corners, and coordinates for accurate spatial AI modeling.
Multi-layer QC, reviewer audits, and automated validation ensure consistent quality.
Yes — 540+ annotators manage millions of images across large AI pipelines.
All workflows follow ISO 27001, HIPAA, and GDPR standards with strict access control.
JSON, CSV, XML, XLSX, TXT, landmark outputs, and client-specific formats.
Yes, teams expand rapidly to meet tight deadlines or volume spikes.
Yes, pilot batches allow quality testing and rule refinement before onboarding.
Share dataset type, volume, and goals to receive a tailored workflow and pricing plan.
Pricing depends on factors like annotation type, dataset size, complexity, turnaround time, and quality level. We offer flexible per-text, per-hour, or per-project pricing.
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