Computer vision

The Center for Vision Technologies

SRI’s Center for Vision Technologies creates fundamental computer vision solutions based on leading-edge technologies, leveraging a wide variety of sensors and computation platforms.

Recent developments from the Center for Vision Technologies 

The Center for Vision Technologies (CVT) develops and applies its algorithms and hardware to be able to see better with computational sensing, understand the scene using 2D/3D reasoning, understand and interact with humans using interactive intelligent systems, support teamwork through collaborative autonomy, mine big data with multi-modal data analytics and continuously learn through machine learning. CVT does both early-stage research and developmental work to build prototype solutions that impact government and commercial markets, including defense, healthcare, automotive and more. Numerous companies have been spun-off from CVT technology successes. 

Recent developments from CVT include core machine learning algorithms in various areas such as learning with fewer labels, predictive machine learning for handling surprise and novel situations, lifelong learning, reinforcement learning using semantics and robust/explainable artificial intelligence. 

SmartVision imaging systems use semantic processing/multi-modal sensing and embedded low-power processing for machine learning to automatically adapt and capture good quality imagery and information streams in challenging and degraded visual environments.

Multi-sensor navigation systems are used for wide-area augmented reality and provide GPS-denied localization for humans and mobile platforms operating in air, ground, naval, and subterranean environments. CVT has extended its navigation and 3D modeling work to include semantic reasoning, making it more robust to changes in the scene. Collaborative autonomy systems can use semantic reasoning, enabling platforms to efficiently exchange dynamic scene information with each other and allow a single user to control many robotic platforms using high-level directives.

Human behavior understanding is used to assess human state and emotions (e.g., in the Toyota 2020 concept car) and to build full-body, multi-modal (speech, gesture, gaze, etc.) human-computer interaction systems. 

Multi-modal data analytics systems are used for fine-grain object recognition, activity, and change detection and search in cluttered environments.

Core technologies and applications

SRI’s Center for Vision Technologies (CVT) tackles data acquisition and exploitation challenges across a broad range of applications and industries. Our researchers work in cross-disciplinary teams, including robotics and artificial intelligence, to advance, combine and customize technologies in areas including computational sensing, 2D-3D reasoning, collaborative autonomy, human behavior modeling, vision analytics, and machine learning. 

Our team

Rakesh “Teddy” Kumar

Vice President, Information and Computing Sciences Director, Center for Vision Technologies

Supun Samarasekera

Senior Technical Director, Vision and Robotics Laboratory, Center for Vision Technologies

Ajay Divakaran

Senior Technical Director, Vision and Learning Laboratory, Center for Vision Technologies

Michael Piacentino

Senior Technical Director, Vision Systems Laboratory, Center for Vision Technologies

Han-Pang Chiu

Technical Director, Vision and Robotics Laboratory, Center for Vision Technologies

Bogdan Matei

Technical Director, Vision and Robotics Laboratory, Center for Vision Technologies

Yi Yao

Technical Director, Vision and Learning Laboratory, Center for Vision Technologies

David Zhang

Senior Technical Manager, Vision Systems Laboratory, Center for Vision Technologies