Title: Deep Learning-Based Human Activity Recognition for Industrial Operations & Robotic Emulation
Abstract:
The ability to recognize, analyze and emulate human activities is becoming increasingly important in a multitude of industries, including robotics, industrial operations, healthcare, sports, and numerous others. The fusion of AI-enabled computer vision and physical sensing is key to this. Ranging from emulation of simple human activities such as training robots to perform a sort, pick and place operations to complex ones such as the assessment of skills of assembly line operators or the technique of sports players, there now exists the ability to recognize and assess human activities for industrial automation or training and improvement of the physical skills of individuals. This presentation will cover the AI technologies at play here, including pose estimation and human action recognition (HAR), and provide an overview of the deep learning algorithms that are used. In addition, a summary of the challenges that are presently being researched will be presented.
Biography:
Vijay Nadkarni is Chief Technology Officer of Movella. He is responsible for Movella’s technology strategy advancement, technological vision, and roadmap. This involves embracing four key areas, namely AI, SaaS, motion sensing, and computer vision. Vijay has over 25 years in technology leadership and management across a wide range of industries. Before Movella, he served as VP of Artificial Intelligence at Tech Mahindra where he headed its AI Practice across 10 diverse verticals. Before that, Vijay was VP of Artificial Intelligence at Visteon for its autonomous driving and infotainment product lines. A veteran of Silicon Valley, Vijay has co-founded multiple startups in AI, motion analytics, and the cloud of which Veraz Networks - a VoIP company - had a NASDAQ IPO. Vijay has an MBA and MSEE, both from Northwestern University, and a BS in Electrical Engineering from IIT-Bombay.