Update README.md

Optimize the description of the Gaze_object_output file

README.md

@@ -53,34 +53,45 @@ Tester1/
 │   └── ...
 
 
+### `Gaze_object_output/`
 
+This directory contains **gaze–object annotation files** for each scene.
+
+**File format**
+- `<scene_id>`: scene index (starting from 0)
+- Each row corresponds to one time step / frame
+
+---
+
+#### Gaze Target Information
+- `Stare_obj`: ID of the object being gazed at  
+  - `0` indicates background or no valid gaze target
+- `Stare_area`: coarse gaze region label on the screen
+
+The screen resolution is **5740 × 1010**, and gaze regions are defined as:
+
+| Label | Description | Region (pixels) |
+|------|-------------|-----------------|
+| `LF` | Left front view | `[0, 0] – [2870, 1010]` |
+| `RF` | Right front view | `[2870, 0] – [5740, 1010]` |
+| `LB` | Left side mirror | `[700, 570] – [1370, 1000]` |
+| `RB` | Right side mirror | `[4719, 560] – [5389, 990]` |
+| `MB` | Rear-view mirror | `[2890, 210] – [3540, 400]` |
 
 ---
 
-## 📊 File Descriptions
-
-### 1. `Gaze_object_output/`  
-- Each `Stare_obj_X.csv` contains **gaze-object interaction results** for subject X.  
-- Typical fields include:
-  - `timestamp`
-  - `object_id`
-  - `gaze_x`, `gaze_y`
-  - `object_class`  
-
-### 2. `Tester2_feature_csv/`  
-- Each `feature_X.csv` provides extracted **feature vectors** for subject X.  
-- Features may cover:
-  - Driver monitoring metrics  
-  - Eye-movement statistics  
-  - Vehicle state parameters  
-
-### 3. `Tester2_IS/`  
-- **`frame_output/`**: Instance segmentation images for each frame (`.png`).  
-- **`obj_pixel_table.csv`**: Pixel-level statistics for segmented background vehicles.  
-  - Example fields:
-    - `object_id`
-    - `pixel_count` (area of mask)
-    - `bbox_x1`, `bbox_y1`, `bbox_x2`, `bbox_y2`
-    - `class_label`
-
----
+#### Vehicle Screen Positions
+- `Car{i}_screen_X`, `Car{i}_screen_Y`: 2D screen-space coordinates of risk-relevant vehicles
+- Coordinates are aligned with the same frame as gaze annotations
+- Missing vehicles are filled with `0`
+
+**Number of risk objects per frame**
+- For the **first 10 participants**, each frame contains up to **9 risk objects**
+- For the **remaining 20 participants**, scenes **5–9** contain **8 risk objects**
+- Columns are kept consistent across files; unused slots are zero-padded
+
+---
+
+These files jointly describe **where the driver is looking** and **where potential risk objects are located** on the screen at each time step, and are time-aligned with other modalities in the dataset.
+
+