
Computer vision
SRI pushes the frontiers of computer vision to enable machines to see, understand and remember. Our end-to-end video and processing technologies make computer vision work in the real world in applications including robotics, vehicles and people-worn systems.
Featured researchers
Core technologies and applications
SRI’s Center for Vision Technologies tackles data acquisition and exploitation challenges across a broad range of industries and applications. Our researchers work on cross-disciplinary teams including robotics and artificial intelligence to advance, combine and customize technologies in areas including:
Computational sensing
Smart vision
Multi-sensor fusion
Embedded, low-power processing
2D-3D reasoning
GPS-denied navigation
3D modeling/mapping
Augmented reality
Surveillance
Biometrics
Collaborative autonomy
Semantic reasoning
Decision-making
AI-based control
Hierarchical planning
Human behavior modeling
Intelligent interactive systems
Human state assessment
Emotion detection
Communicating with computers
Human activity understanding
Vision analytics
Image and video search
Activity recognition
Fine-grain recognition
Social media analytics
Radio frequency machine learning (RFML)
Machine learning
Explainable AI
Lifelong learning
Creative AI
Approximate computing
Robust AI
Publications
Motion Adaptive Signal Integration-High Dynamic Range (MASI-HDR) Video Processing for Dynamic Platforms
SRI Authors: Michael Piacentino
Conference Paper May 1, 2013
Depth Extraction from Videos Using Geometric Context and Occlusion Boundaries
SRI Authors: Harpreet Singh Sawhney
Conference Paper February 1, 2015
AR-Mentor: Augmented Reality Based Mentoring System
SRI Authors: Louise Yarnall, Supun Samarasekera, Rakesh “Teddy” Kumar
Conference Paper September 1, 2014
Precise Vision-Aided Aerial Navigation
SRI Authors: Supun Samarasekera, Han-Pang Chiu
Conference Paper September 1, 2014

SRI offers a unique blend of academia and industry, which offers an opportunity to work on problems that involve research and are practically relevant.
Karan Sikka
Computer Scientist, Information & Computing Sciences
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