Human Pose Estimation in Computer Vision

The Research and Consultancy Committee of the IT department has organized a webinar titled "Human Pose Estimation in Computer Vision" on November 10th 2022. The webinar was delivered by Dr. Bharatesh Chakravarthi, a renowned researcher in the field of computer vision and human pose estimation. The webinar aimed to provide an overview of human pose estimation techniques in computer vision, their applications, and current research trends.
Key Takeaways:

• Introduction to Human Pose Estimation: Dr. Chakravarthi started the webinar by introducing the concept of human pose estimation in computer vision. He explained that human pose estimation is the process of estimating the position, orientation, and configuration of a person's body parts in an image or video. He also discussed the importance of human pose estimation in various applications such as robotics, gaming, healthcare, and surveillance.
• Techniques for Human Pose Estimation: Dr. Chakravarthi explained various techniques used for human pose estimation, including 2D pose estimation, 3D pose estimation, and multi-person pose estimation. He discussed the advantages and limitations of each technique and also shared some recent advancements in these areas.
• Applications of Human Pose Estimation: The webinar also covered various applications of human pose estimation, including action recognition, gait analysis, human-computer interaction, and sports analysis. Dr. Chakravarthi explained how these applications are benefiting from human pose estimation techniques and shared some examples of successful implementations.
• Challenges and Future Directions: In the final part of the webinar, Dr. Chakravarthi discussed the current challenges and future directions of human pose estimation research. He highlighted some of the major challenges such as occlusion, variability in human body shapes and sizes, and the need for large annotated datasets. He also discussed some of the recent research trends, such as deep learning-based approaches, multi-modal fusion, and the use of generative model

Conclusion:
In conclusion, the webinar "Human Pose Estimation in Computer Vision" provided valuable insights into the current state-of-the-art techniques and applications of human pose estimation in computer vision. The webinar was well-structured and informative, and Dr. Chakravarthi did an excellent job of explaining complex concepts in an easy-to-understand manner. Overall, the webinar was a great learning experience and provided a better understanding of the importance and challenges of human pose estimation in computer vision.
Around 230 participants attended the webinar from various institutes in Oman and India. The overall feedback provided by the participants was 4.6 out of 5