International Journal of Advanced Research in Computer and Communication Engineering

Abstract: The rapid growth of intelligent camera applications has increased the demand for automated and user-friendly image capturing systems. Conventional selfie capturing methods require manual interaction, which may lead to poor timing, blurred images, or unnatural facial expressions. To overcome these limitations, this project presents an Auto Selfie Capture by Smile system that automatically captures a photograph when a user smiles.
The proposed system utilizes computer vision and machine learning techniques to detect human faces and recognize smiling expressions in real time using a live camera feed. Haar Cascade classifiers are employed for efficient face and smile detection. Once a smile is detected and maintained for a predefined duration, the system automatically captures and stores the selfie image without any user intervention. Additional checks such as face alignment and stability help improve image quality and reduce false captures.
This system provides a hands-free, accurate, and efficient solution for selfie capturing, making it suitable for applications in smart cameras, mobile devices, and human–computer interaction systems. The proposed approach is lightweight, cost-effective, and capable of real-time performance on standard hardware.

Keywords: Auto Selfie Capture, Smile Detection, Face Detection, Computer Vision, OpenCV, Haar Cascade Classifier, Image Processing, Human–Computer Interaction.

Downloads: | DOI: 10.17148/IJARCCE.2026.15162