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video-analysis-workflow

Guides video analysis for CMJ and drop jump. Use when processing athlete videos, debugging pose detection, troubleshooting analysis failures, or running kinemotion CLI commands.

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KinemotionInc/kinemotion
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2026년 1월 16일 04:26
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name
video-analysis-workflow
description
Guides video analysis for CMJ and drop jump. Use when processing athlete videos, debugging pose detection, troubleshooting analysis failures, or running kinemotion CLI commands.
allowed-tools
Bash(uv run kinemotion:*), Read, Glob
# Video Analysis Workflow ## Analysis Commands ```bash # CMJ analysis uv run kinemotion cmj-analyze <video> [--output debug.mp4] # Drop Jump analysis uv run kinemotion dropjump-analyze <video> [--output debug.mp4] # Batch processing uv run kinemotion cmj-analyze videos/*.mp4 --batch --workers 4 ``` ## Quality Presets | Preset | Use Case | Trade-off | | ---------- | ---------------------------- | --------------------- | | `fast` | Quick preview, large batches | Lower accuracy | | `balanced` | Default, most use cases | Good accuracy/speed | | `accurate` | Validation, research | Best accuracy, slower | ```bash uv run kinemotion cmj-analyze video.mp4 --quality accurate ``` ## Debug Output Always use `--output debug.mp4` when: - Metrics seem incorrect - Troubleshooting pose detection - Validating new videos - Training coaches on video quality The debug video shows: - Skeleton overlay with joint angles - Phase markers (takeoff, landing, peak) - Real-time metrics display ## Camera Angle Recommendations | Angle | Recommendation | Reason | | --------------- | --------------- | ---------------------------------------------- | | **45° oblique** | Recommended | Both legs clearly visible, accurate tracking | | 90° lateral | Not recommended | MediaPipe confuses left/right feet (occlusion) | | Front/back | Not recommended | Depth ambiguity for sagittal plane motion | ## Troubleshooting ### No Takeoff Detected 1. Verify video contains complete jump (before, during, after) 2. Check athlete is fully visible throughout 3. Try `--quality accurate` for stricter detection 4. Review debug video for landmark quality ### Invalid Metrics 1. Video may be too short (need full jump cycle) 2. Athlete may be partially occluded 3. Poor lighting affecting pose detection 4. Camera shake causing landmark jitter ### Jittery Landmarks 1. Check lighting conditions (avoid backlighting) 2. Ensure stable camera (tripod recommended) 3. Verify athlete clothing contrast with background 4. Try `--quality accurate` for better filtering ### Rotation Issues (Mobile Videos) - Mobile videos often have rotation metadata - kinemotion handles this automatically via `video_io.py` - If issues persist, pre-process with: `ffmpeg -i input.mp4 -vf "transpose=1" output.mp4` ## Video Requirements | Requirement | Specification | | ----------- | -------------------------- | | Frame rate | 30+ fps (60+ preferred) | | Resolution | 720p minimum | | Duration | Full jump cycle visible | | Lighting | Even, front-lit preferred | | Background | Contrasting with athlete | | Camera | Stable, tripod recommended | ## Output Metrics ### CMJ Metrics - `jump_height_cm`: Calculated from flight time - `flight_time_ms`: Time in air - `countermovement_depth_cm`: Lowest point before takeoff - `takeoff_velocity_m_s`: Velocity at ground leave - `triple_extension`: Hip, knee, ankle angles at takeoff ### Drop Jump Metrics - `ground_contact_time_ms`: Time on ground after drop - `flight_time_ms`: Time in air after contact - `reactive_strength_index`: RSI = flight_time / contact_time - `drop_height_cm`: Initial drop height (if detectable) ## Python API Alternative ```python from kinemotion import process_cmj_video, process_dropjump_video # CMJ metrics = process_cmj_video("video.mp4", quality="balanced") # Drop Jump metrics = process_dropjump_video("video.mp4", quality="balanced") ```
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