Datasets:
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)
Data Collection:
Real human video recorded for confidence behavior analysis.Pose Extraction:
MediaPipe Holistic model used to extract body and facial landmarks.Feature Engineering:
Computation of geometric ratios and angles such as eye-to-shoulder ratio, hip-shoulder difference, body lean, spine angle, and head tilt.Label Assignment:
Rule-based labeling (posture and facial cues) with human validation.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.
🧾 License
MIT License — free for research and educational use.