Leverage advanced computer vision and deep learning with OpenPose to create scalable pose detection systems that enhance user experience, enable real-time tracking, and drive innovation across industries like AR, fitness, and surveillance.
OpenPose is an open-source library for real-time multi-person keypoint detection, capable of detecting 135 keypoints (body, face, hands, feet) in images and videos. Our development services integrate OpenPose with custom models, enabling precise pose estimation for applications in computer vision, from fitness tracking to AR/VR interactions.
Simplified OpenPose Architecture Flow
Process multiple poses simultaneously with low latency for live applications.
Handle complex scenes with unlimited people without performance degradation.
Tailor models and APIs for seamless embedding in your existing systems.
Deploy across web, mobile, edge devices, and cloud platforms effortlessly.
Extract insights from pose data to optimize user interactions and business metrics.
Ensure privacy with encrypted processing and compliance to GDPR/HIPAA standards.
A streamlined, iterative workflow to deliver robust OpenPose solutions tailored to your needs.
1
Analyze requirements, define keypoints, and map use case scenarios.
2
Create pose flows and build MVP with OpenPose integration.
3
Implement models, APIs, and multi-device support.
4
Conduct QA, measure accuracy, and refine based on feedback.
5
Launch with continuous analytics and updates for evolving needs.
Comprehensive body, face, hand, and foot tracking for detailed analysis.
Simultaneously detect and analyze multiple individuals in real-time.
High-speed inference for live video streams and interactive apps.
Fine-tune models for domain-specific accuracy and performance.
RESTful APIs for easy embedding in web, mobile, and IoT devices.
On-device processing for privacy-focused, low-bandwidth applications.