Update README.md

README.md

@@ -43,11 +43,11 @@ dataset_info:
 | | |
 |---|---:|
 | **Duration** | **1000+ hours** @ 120 Hz |
-| **Scenarios ** | 15+ real-world scenes |
-| **Tasks ** | 500+ standardized tasks |
+| **Scenarios** | 15+ real-world scenes |
+| **Tasks** | 500+ standardized tasks |
 | **Objects** | 200+ tracked props (6D pose) |
-| **Modalities** | Skeleton · Finger · Object 6D · Video · Labels |
-| **Formats ** | BVH · Retargeted CSV · NPZ |
+| **Modalities** | Skeleton · Object 6D · Video · Labels |
+| **Formats** | BVH · Retargeted CSV · NPZ |
 
 ✅ **Access note:** This dataset is fully open and publicly accessible.  
 
@@ -55,9 +55,7 @@ dataset_info:
 
 ## Key Features 
 
-- **Optical ground truth** – sub-mm accuracy, 120 fps, no estimation errors.  
-
-- **Dexterous hands** – 20+ DoF per hand, synchronized with object 6DOP pose.  
+- **Optical ground truth** – sub-mm accuracy, 120 fps, no estimation errors.    
 
 - **Robot-ready** – pre-retargeted to Unitree G1; custom retargeting available.  
 
@@ -80,11 +78,11 @@ ChingMu 1000H is an optical motion capture dataset designed for training and val
 
 | Component | Format | Details |
 |---|---|---|
-| Raw motion | `.bvh` | Y-up, 120 fps, ZYX rotation, cm, 47–67 joints |
+| Raw motion | `.bvh` | Y-up, 120 fps, YXZ rotation, cm, 22 joints |
 | Retargeted trajectories | `.csv` | Root position (m), quaternion, joint angles (rad) |
 | Object 6D pose | `.csv` | Position (m) + quaternion, 120 Hz |
-| Multi-view video | `.mp4` | 4–8 cameras, co-registered |
-| Semantic labels | `.jsonl` | Task, scenario, action, object |
+| Multi-view video | `.mp4` | 2-3 cameras, co-registered |
+| Semantic labels | `.csv` | Task, scenario, action, object |
 
 
 ## 🎥 Preview Video