Every question the AI Motion pages answer
The 13 ai motion pages answer 65 named questions between them. Every one is listed below, and every link lands on the paragraph that answers it rather than the top of the page.
Pose Estimation Models Compared: MediaPipe, MoveNet, YOLO and More
- How many keypoints does each model detect?MediaPipe/BlazePose predicts 33 body landmarks, a superset of the 17 COCO keypoints that adds face, hand, and foot points. MoveNet,…
- Which model should I use for a single-user fitness app?For a single user on-device, MediaPipe/BlazePose is the common default: its 33 landmarks and monocular 3D world landmarks suit joint-angle…
- Are these pose models free to use commercially?Not all of them. MediaPipe/BlazePose, MoveNet, and PoseNet are Apache-2.0, the most permissive here, though you should still verify terms…
- Which of these models output 3D landmarks?Among the common on-device options, only MediaPipe/BlazePose: alongside its 2D image-coordinate landmarks it returns 3D world landmarks in…
- Which models handle multiple people at once?YOLO-pose detects multiple people and their keypoints in one pass, and OpenPose is a bottom-up multi-person system. MediaPipe/BlazePose and…
- Should I pick MoveNet or MediaPipe for a fitness app?They sit at different points on the same trade-off. MediaPipe Pose (BlazePose) returns 33 keypoints including monocular 3D world landmarks,…
2D vs 3D Pose Estimation for Fitness Apps
- Do I need a depth camera or LiDAR for 3D pose?No. A normal RGB phone camera is enough for both 2D pose and monocular 3D world landmarks — models like BlazePose infer depth from a single…
- How reliable is monocular 3D depth?Less reliable than the x and y axes, and less reliable than multi-camera or depth-sensor 3D. Predicting true depth from one image is…
- When is 2D enough and when do I need 3D?2D is enough when the joint angle you measure stays in the camera plane — for example an elbow angle filmed side-on or a knee angle filmed…
- Is 3D form feedback accurate enough for injury or medical advice?No. Camera-based form feedback, whether 2D or monocular 3D, is a coaching aid, not medical or physical-therapy advice. Monocular depth…
Pose Estimation Accuracy: What It Means and What Drives It
- What do PCK, OKS, and MPJPE measure?PCK (Percentage of Correct Keypoints) is the fraction of 2D keypoints within a distance threshold of ground truth, with the PCKh variant…
- What degrades pose estimation accuracy the most?Low or backlit lighting, occlusion of joints behind the body or objects, extreme camera angles, too much distance from the camera, loose or…
- How do confidence and visibility scores help?Pose models emit a per-keypoint confidence or visibility score (some, like BlazePose, add a presence score) that indicates how sure the…
- What is the One-Euro filter and why is it used?The One-Euro filter is a low-pass filter with an adaptive cutoff used to reduce frame-to-frame jitter in real-time pose tracking. It…
- How do I evaluate accuracy for my own app?Do not trust a leaderboard score alone. Record footage that matches production (your camera, your users' lighting, distances, angles,…
Multi-Person Pose Tracking: Top-Down vs Bottom-Up
- What is the difference between top-down and bottom-up pose estimation?Top-down first detects each person, then runs a pose model on each cropped box, so per-person accuracy is generally higher but inference…
- Does my fitness app need multi-person pose tracking?Usually not. Most fitness apps are single-user, with one person in front of one camera, and single-person models such as…
- Which models support multi-person pose?OpenPose is the classic bottom-up multi-person system using Part Affinity Fields to group keypoints. YOLO-pose (Ultralytics) is…
- How are people tracked across frames?Per-frame pose estimation does not by itself keep identities stable, so multi-person work adds a separate tracking layer that associates…
- Are there licensing concerns with multi-person models?Yes, and they are a real decision point. OpenPose ships under a non-commercial/academic research license, so commercial use requires a…
On-Device vs Cloud Pose Estimation: Which to Choose
- Is on-device or cloud pose estimation better for a fitness app?For most consumer fitness apps, on-device is the better default. Running the model on the phone with a toolkit like ML Kit Pose,…
- Why is streaming workout video to a server a privacy concern?A workout video is raw footage of a person's body, face, and home - sensitive personal and biometric data, not a neutral rep count. When…
- Can I keep video private but still use a server?Yes, with a hybrid architecture. Run pose detection on the edge device, then transmit only the text-based landmark coordinates - not the…
- Does cloud pose estimation cost more than on-device?Generally yes, in a recurring way. On-device inference runs on hardware the user already owns, so there is no per-frame server bill. Cloud…
- Does on-device pose estimation work on older phones?It can, but performance depends on the device. Phones with a strong GPU or neural accelerator run pose models smoothly, while older or…
Real-Time Pose Estimation: Frame Rate, Latency, and Model Trade-offs
- What frame rate do I need for real-time pose estimation?Smooth, interactive tracking is commonly framed around 30 fps, but usable coaching can work at lower rates, so treat any single number as a…
- Should I use MoveNet Lightning or Thunder?Lightning is tuned for speed with a smaller model and lower input resolution, so it suits live rep counting, real-time overlays, and…
- What should I do if inference can't keep up with the camera?Drop frames rather than queue them. If you queue frames the model can't process in time, feedback drifts further and further behind the…
- Why is temporal smoothing needed?Per-frame pose estimation jitters, so the keypoints wobble even when the subject holds still, and raw keypoints are too noisy to derive…
- Does continuous pose estimation drain the battery?Yes. A continuous camera plus continuous inference is a sustained load that drains battery and heats the device over a full workout, and a…
Pose Estimation Hardware Requirements: What You Actually Need
- Do I need a depth camera or LiDAR for pose estimation?No. A normal RGB smartphone camera is enough for 2D pose and for monocular (single-camera) 3D pose - both run from a single RGB frame.…
- Does pose estimation need a GPU or a special AI chip?It runs faster and uses less battery with one, but it is not strictly required. Hardware acceleration - a mobile GPU, or an NPU/Neural…
- Will pose estimation work on older or low-end phones?Often yes, but expect lower frame rates. Older and budget devices lack an NPU and have weaker GPUs and CPUs, so heavier models can drop…
- What hardware do I need to run pose estimation in the cloud?Server-side pose inference typically needs GPU hardware to run heavier models at frame rate, which is a recurring per-frame or per-minute…
- Do lighting and camera position affect the hardware I need?They affect accuracy more than they change the hardware, but they matter a lot. Accuracy degrades in low light, backlight, and harsh…
How Rep Counting Works: The Algorithm Explained
- What signal does a rep counter actually track?It reduces the pose to one number that oscillates once per rep. Most commonly that is a joint angle from three keypoints (elbow angle for a…
- What is hysteresis and why does it stop double-counting?Hysteresis means using two different thresholds with a gap between them instead of one. To count a rep you must cross a low threshold into…
- How do you handle noise and false reps?Smooth the keypoints or the derived angle before any detection (a One Euro filter is a common low-cost choice), use hysteresis rather than…
- Do I need a depth camera to count reps?No. A normal RGB phone camera is enough. Rep counting tracks 2D joint angles that stay in the camera plane, so no depth sensor or LiDAR is…
- How accurate is camera-based rep counting?It varies by exercise, dataset, and the user's form, so there is no single number to quote. Partial reps, very fast reps, occlusion, and…
How Camera-Based Form Feedback Works
- How does a form checker actually measure my form?It takes three keypoints that meet at a joint (for a squat, hip, knee, and ankle), computes the angle between the two limb segments, and…
- Do I need a depth camera or special sensor for form feedback?No. A normal RGB phone camera is enough to track keypoints and compute joint angles. No LiDAR or depth sensor is required. The catch is…
- Can I use camera form feedback for injury rehab or physical therapy?Treat it only as general coaching, never as medical or physical-therapy advice. Monocular pose estimation is not accurate enough for…
- Why does form feedback get worse from some camera angles?Any joint angle that projects toward or away from the camera falls into the depth axis, which is exactly where a single-camera estimate is…
- How accurate is camera-based form feedback?Good enough for gross-movement coaching, not for degree-level or clinical claims. Accuracy depends on lighting, clothing, camera angle,…
Build vs Buy: AI Motion Tracking
- Isn't the hard part just picking a pose model?No. Choosing MediaPipe, MoveNet, or Apple Vision is the easy first step. The real, ongoing work is everything after the keypoints arrive:…
- When does building your own pipeline make sense?Build when camera-based motion tracking is your core differentiator, you have computer-vision/ML engineers, you need offline use and zero…
- What does buying a motion-tracking SDK cost?A recurring per-user or per-device fee, plus less control over the underlying model and its roadmap. Free tiers and paid plans both exist,…
- Can I mix building and buying?Yes, and most teams do. The common hybrid is to adopt an on-device pose model or SDK for detection, then build your own rep, form, and…
- Do I need a depth camera either way?No. A normal RGB phone camera is enough for both 2D and monocular 3D pose, whether you build or buy. Monocular 3D depth is estimated rather…
MediaPipe vs MoveNet: Decide by What You Compute Downstream
- Does MoveNet output any 3D or depth information?No. MoveNet's model card documents 17 COCO keypoints as 2D normalized coordinates with a confidence score per keypoint, and nothing else.…
- Can MediaPipe Pose track multiple people like MoveNet MultiPose?The BlazePose GHUM model card states it tracks only one person when multiple are on scene, while MoveNet MultiPose Lightning is documented…
- Is MoveNet still maintained in 2026?It looks stable and frozen rather than actively developed. The last commit touching pose-detection in the tensorflow/tfjs-models repo was…
- Which is actually faster, MediaPipe Lite or MoveNet Lightning?No published number answers that honestly. BlazePose's card reports FPS on a Pixel 3 via TFLite, while MoveNet's card reports milliseconds…
- Are MediaPipe's world landmarks accurate in real meters?Treat them as scaled estimates, not measurements. Google documents world landmarks as real-world 3D coordinates in meters with the origin…
MediaPipe Pose Landmarker Models: Lite vs Full vs Heavy
- Can I swap Pose Landmarker variants without changing code?Mostly yes, and that is the point of the family. All three variants emit the same 33 landmarks with the same per-landmark values (x, y, z,…
- What does the /latest/ segment in the Pose Landmarker model URL mean?It is the version slot in the download path on Google's mediapipe-models storage bucket - a pointer to the newest published build rather…
- Why is the pose_landmarker .task file bigger than the model size in the model card?The model card's figures - 3 MB lite, 6 MB full, 26 MB heavy - describe the landmark models alone, while the .task downloads are bundles…
- What does float16 mean in the Pose Landmarker download path?It is the precision segment of the path - it names the numeric precision of the bundled model weights, in this case half-precision floating…
- Does pose_landmarker_heavy add extra landmarks or multi-person tracking?No. Heavy outputs the same 33 landmarks as lite and full, and the model card states the model tracks only one person on scene if multiple…
Apple Vision Framework Body Pose: The Native iOS Option
- Why do Apple's 2D and 3D body pose requests return different joint counts?They use different skeletons. VNDetectHumanBodyPoseRequest exposes 19 named joint constants including face detail (nose, eyes, ears) plus…
- Does Apple publish a model card or accuracy numbers for Vision body pose?No. Apple's documentation is an API reference: it contains no model card, no accuracy figures, no evaluation dataset, no…
- What OS versions do the Vision body pose requests require?Apple documents VNDetectHumanBodyPoseRequest (2D) as available from iOS 14.0, iPadOS 14.0, macOS 11.0, Mac Catalyst 14.0, tvOS 14.0, and…
- Can Vision run body pose on recorded video instead of a live camera?Yes. VNVideoProcessor is Apple's documented object for offline analysis of video content: create it with init(url:) pointing at a video…
- Should a cross-platform fitness app use Apple Vision for pose estimation?Usually not as its only pose layer. Vision runs on Apple platforms only, so an Android sibling app needs a second implementation with a…
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