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Towards Fault-Aware Image Captioning: A Review on Integrating Facial Expression Recognition (FER) and Object
Abdul Saboor Khan1, Muhammad Jamshed Abbass2, Abdul Haseeb Khan3
1Department of Electrical Engineering and Information Technology, Otto-von-Guericke University, 39106 Magdeburg, Germany.
Sensors (Basel, Switzerland)
|October 16, 2025
Summary
This review explores image captioning for Industry 4.0, focusing on facial expressions and object detection for fault-aware Prognostics and Health Management (PHM) systems. It highlights current methods and future research directions for enhanced industrial monitoring.
Area of Science:
- Computer Vision and Natural Language Processing
- Artificial Intelligence in Industrial Applications
- Prognostics and Health Management (PHM)
Background:
- Image captioning, converting images to text, is advancing with Vision Transformers (ViT), BERT, and GPT.
- Despite abundant visual data, image captioning remains an open research area, especially for industrial contexts.
- Existing research often overlooks the significance of operator facial expressions in industrial image captioning.
Purpose of the Study:
- To review the current state of image captioning, emphasizing facial expression recognition and object detection.
- To explore applications in fault-aware systems and Prognostics and Health Management (PHM) within Industry 4.0.
- To identify research gaps, particularly concerning the role of facial expressions in industrial fault detection.
Main Methods:
- Review of fault-aware methodologies leveraging visual data for PHM in smart manufacturing.
- Analysis of approaches combining facial expression recognition and object detection for image captioning.
- Evaluation of the advantages and disadvantages of various image captioning strategies in industrial settings.
Main Results:
- Facial expressions and object detection offer valuable insights for fault detection and system health monitoring in Industry 4.0.
- Fault-aware methodologies utilizing visual data are crucial for PHM in smart manufacturing.
- Current image captioning techniques show promise but require further refinement for industrial accuracy.
Conclusions:
- Facial expression analysis in image captioning is critical for industrial fault detection and PHM.
- Future research should focus on developing more detailed and accurate machine-translated captions for Industry 4.0.
- Enhanced image captioning systems can significantly improve diagnostics and maintenance in smart manufacturing environments.
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