Oodles AI builds production-ready pose estimation systems using OpenPose and GPU-accelerated deep learning pipelines. We help organizations deploy real-time, multi-person keypoint detection solutions for fitness, safety monitoring, AR/VR, and analytics-driven applications.
OpenPose is an open-source framework for real-time, multi-person pose estimation that detects up to 135 body, face, hand, and foot keypoints from images and video streams. At Oodles AI, we engineer OpenPose-based systems with optimized inference, GPU acceleration, and scalable APIs for accurate pose intelligence across devices.
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.
Privacy-first pose analytics with encrypted pipelines and compliance-ready processing without storing facial identity data.
Oodles AI combines the OpenPose engine with real-time streaming, edge deployment, and analytics dashboards to capture and analyze human movement at scale across consumer and enterprise platforms.
Deliver studio-quality posture feedback for fitness, yoga, and physiotherapy apps with real-time scoring overlays.
Track athletes or crowds across multiple cameras, sync with wearables, and surface tactical heatmaps instantly.
Detect unsafe body positions on factory floors, trigger SOP alerts, and preserve audit trails for regulators.
Power photoreal avatars, volumetric concerts, and collaborative workspaces with low-latency full-body tracking.
Translate pose metrics into clinician-friendly charts and automate progress tracking for remote care programs.
Fuse OpenPose data with PLCs and ROS stacks to orchestrate cobots, AGVs, and digital workers safely.
Rapid prototypes and production engagements spanning consumer, enterprise, and public-sector scenarios.
Pose-aware workout scoring, balance analysis, and automated rep detection for premium subscriber experiences.
Use OpenPose to detect unsafe body postures, ergonomic risks, and restricted zone violations without relying on facial recognition.
Enable controller-free inputs, synchronized avatars, and haptics-ready data streams for XR headsets.
Pose-based monitoring of driver posture, fatigue, and cabin movement using OpenPose keypoint tracking.
Streamline gait analysis, joint-angle tracking, and tele-rehab evidence with HIPAA-aligned pipelines.
Measure dwell time, shopper engagement, and queue ergonomics without invasive facial data.
A structured delivery process focused on OpenPose model tuning, real-time inference optimization, and scalable deployment.
1
Analyze camera inputs, keypoint requirements, latency targets, and deployment constraints.
2
Prototype pose pipelines and validate OpenPose inference accuracy.
3
Integrate OpenPose models with APIs, streaming layers, and multi-device runtimes.
4
Optimize GPU performance, reduce latency, and validate pose accuracy.
5
Deploy OpenPose pipelines with monitoring, analytics, and continuous updates.
Comprehensive body, face, hand, and foot tracking for detailed analysis.
Simultaneously detect and analyze multiple individuals in real-time.
GPU-accelerated OpenPose inference using CUDA and TensorRT for real-time video processing.
Fine-tuning OpenPose models and post-processing logic for domain-specific pose accuracy.
RESTful APIs for easy embedding in web, mobile, and IoT devices.
On-device processing for privacy-focused, low-bandwidth applications.
Oodles AI engineers OpenPose solutions across GPU, CPU, and edge environments with hardened CI/CD pipelines for real-time pose estimation workloads.