---
pretty_name: ConfiDetect Confidence Posture Dataset
license: mit
language:
  - all   
task_categories:
  - tabular-classification
tags:
  - computer-vision
  - pose-estimation
  - human-behavior
  - mediapipe
  - affective-computing
  - machine-learning
  - confidence-detection
size_categories:
  - 1K<n<10K
---


# 🧍‍♂️ ConfiDetect Confidence Posture Dataset

### Subtitle
**Pose-based Confidence Estimation Dataset for Behavioral and Affective Computing**

---

## 📘 Overview

The **ConfiDetect Confidence Posture Dataset** contains normalized geometric and ratio-based features extracted from human posture and facial keypoints to classify **confidence levels** — *Low*, *Neutral*, and *Confident*.

This dataset was created as part of the **ConfiDetect Tool**, designed to evaluate human confidence through pose and body-language cues using computer vision.
  
---

## 🧩 Dataset Information

- **Total Samples:** 5,950  
- **Features:** 18 (15 numeric + 3 categorical)  
- **Target Classes:** Low, Neutral, High Confidence  
- **Format:** CSV  
- **Normalization:** Min–Max scaling applied  
- **Class Balance:** 53% High, 28% Neutral, 19% Low     

---

## 🧠 Methodology (Concise)

1. **Data Collection:**  
   Real human video recorded for confidence behavior analysis.

2. **Pose Extraction:**  
   MediaPipe Holistic model used to extract body and facial landmarks.

3. **Feature Engineering:**  
   Computation of geometric ratios and angles such as eye-to-shoulder ratio, hip-shoulder difference, body lean, spine angle, and head tilt.

4. **Label Assignment:**  
   Rule-based labeling (posture and facial cues) with human validation.

5. **Normalization:**  
   All numeric attributes normalized for ML model compatibility.

---

## 📁 File Description

| Column Name | Type | Description |
|--------------|------|-------------|
| eye_shoulder_y_ratio | float | Ratio between eye and shoulder Y-axis positions |
| shoulder_y_diff | float | Shoulder height difference |
| wrist_distance_x | float | Horizontal distance between wrists |
| wrist_shoulder_ratio | float | Wrist distance normalized by shoulder span |
| nose_eye_center_offset_x | float | Horizontal offset of nose from eye center |
| shoulder_span | float | Distance between left and right shoulders |
| hip_shoulder_y_diff | float | Difference between hip and shoulder alignment |
| body_lean_x | float | Forward/backward lean of upper body |
| shoulder_center_x | float | X-coordinate of shoulder midpoint |
| hip_center_x | float | X-coordinate of hip midpoint |
| spine_angle | float | Vertical spine inclination angle |
| eye_distance | float | Distance between eyes |
| head_tilt_angle | float | Head tilt angle in degrees |
| eye_distance_ratio | float | Normalized eye distance ratio |
| shoulder_slope | float | Slope between shoulders |
| head_direction | object | Head orientation (Left, Right, Straight) |
| arm_position | object | Arm posture (Open, Closed, Partially Open) |
| posture | object | Overall body posture description |
| confidence_label | object | Target class: Low, Neutral, High |

---

## 🧮 Suggested Use

- **Confidence Estimation Models**
- **Behavioral Analysis**
- **Affective Computing**
- **Body-Language Recognition**
- **Human-Computer Interaction Research**

---

## 📊 Example Tasks

- Train classifiers (e.g., Random Forest, XGBoost, or SVM) to predict confidence.  
- Build pose-based deep learning models with feature fusion.  
- Evaluate correlations between physical posture and perceived confidence.

---

## 📜 Citation

```
Khubaib (2025). ConfiDetect-Confidence-Posture-Dataset: Pose-based Confidence Estimation using MediaPipe Features. Hugging Face.
```

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## 🧾 License

**MIT License** — free for research and educational use.