PoseTracker AI vs MiSensorKit

PoseTracker AI lets you experience PoseTracker’s real-time pose estimation directly on your iPhone before integrating it into your own product. No login, no setup – just install and start playing with the API. Switch between Live camera and Video upload to see how PoseTracker tracks movement in different contexts. The app renders a clean overlay with metrics so you can feel exactly what your users would see in a production app. Explore a built-in exercise library with ready-made logic for repetition exercises, static holds, and custom jump flows. PoseTracker counts reps, measures hold duration and evaluates form quality so you don’t have to design pose logic from scratch. For jumps, PoseTracker turns motion into numbers: air time, jump height and summaries over a session. You can enter a user’s height when needed, or run pure physics-based jump analysis. This demo shows exactly what you get from the PoseTracker API: pose estimation, exercise detection, jump analysis and per-frame metrics – all wrapped in a mobile-ready experience you can plug into your own app. What you can try in this app - Real-time pose estimation via the device camera - Video upload analysis for recorded workouts - Rep counting and form grading for dynamic exercises - Duration tracking for static holds (like planks or wall sits) - Jump analysis with air time and jump height metrics - A developer-friendly UI that mirrors a typical in-app integration

MiSensorKit is a multi-modal field recording application designed for iOS devices. It enables synchronized capture of multiple sensor streams within a single recording session, making it the ideal portable tool for building rich multi-modal datasets in the field. CAPTURE MULTIPLE MODALITIES RGB frames saved as high-resolution JPEGs (up to 1024px) LiDAR depth maps stored as UInt16 millimeter buffers Full camera intrinsics and 6-DoF extrinsic pose logged every frame as JSON Real-time 3D body skeleton tracking with joint positions via ARKit Front-facing selfie camera capture Gaze estimation and eye tracking data GPS location with latitude, longitude, altitude, speed, heading, and accuracy metrics IMU data including accelerometer, gyroscope, fused attitude (roll/pitch/yaw), and gravity vector Ambient light intensity and color temperature estimates Barometric pressure readings synchronized with every frame FLEXIBLE RECORDING SETUP Choose which modalities to record, configure sampling frequency from 1 to 60 Hz, and select output resolution from 224 to 1024 px. A built-in preflight check alerts you to missing permissions or hardware limitations before you start. Monitor sensor status, live FPS, stream health, and session size in real time while recording. BUILT-IN DATA VIEWER Browse and inspect recorded sessions directly on your device. Scrub through individual frames to view RGB images, depth maps, camera metadata, skeleton data, and sensor readings — without needing to transfer files to a computer. EXPORT AND SHARE Export any session as a ZIP archive directly from the app, or share the raw folder via Files and AirDrop. A session summary sheet appears automatically after each recording with key statistics and one-tap sharing options. STRUCTURED OUTPUT FORMAT Each recording session creates an organized folder structure with separate directories for RGB, depth, camera pose, skeleton, GPS, IMU, and metadata — ready for your processing pipeline. REQUIREMENTS iPhone or iPad with LiDAR sensor (required for depth recording only) iOS 26.0 or later Designed for researchers and developers who need a portable, easy-to-use tool for multi-modal data collection without external hardware or complex calibration setups.