Aniket Bharati

Papers

Total Citations

H-Index

About

Aniket Bharati is a researcher whose work sits at the intersection of computer vision, biometrics, and cybersecurity. His most-cited paper, “Surveillance Robots based on Pose Invariant Face Recognition Using SSIM and Spectral Clustering” (2018, 5 citations), tackles a critical challenge in real-world security: making face recognition systems robust to variations in head pose. By integrating Structural Similarity Index (SSIM) with spectral clustering, Bharati proposed a method that improves identification accuracy even when subjects are not directly facing the camera—a common scenario in surveillance. This contribution is particularly relevant for autonomous security robots, where reliable, pose-invariant recognition is essential for authentication and threat detection. While his citation count is modest, the work highlights a practical, application-driven approach to biometrics, bridging the gap between algorithmic robustness and deployable systems. For students and researchers exploring face recognition under unconstrained conditions, Bharati’s work offers a clear example of how combining classical image quality metrics with clustering techniques can enhance real-world performance. His research underscores the ongoing need for resilient, pose-adaptive solutions in modern cybersecurity and robotics.