Blessy Chacko
Papers
1
Total Citations
25
H-Index
1
About
Dr. Blessy Chacko is a leading researcher in computer vision and video surveillance, with a focus on advancing object detection and tracking methodologies. Her most-cited work, "Hybrid object detection using improved three frame differencing and background subtraction" (2017, 25 citations), introduces a novel hybrid approach that combines enhanced three-frame differencing with background subtraction to improve motion-based recognition in video sequences. This technique addresses critical challenges in robotics, human-computer interaction, and surveillance systems by enabling more accurate and robust detection of moving objects. Dr. Chacko’s contributions have been instrumental in refining motion-based detection algorithms, offering a practical solution for real-time applications where traditional methods often falter. Her work demonstrates a deep understanding of the interplay between frame differencing and background modeling, paving the way for more efficient and reliable video analysis. With a growing citation record, Dr. Chacko continues to influence the field, providing foundational insights that support advancements in autonomous systems and security technologies. Her research remains a valuable resource for students and engineers seeking to enhance object detection in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1