Simultaneous localization and mapping (SLAM) technology has been evolving for quite some time, including visual SLAM, which relies primarily on image data. But implementing fast, accurate visual SLAM in embedded devices has been challenging due to high compute and precision requirements. Recent improvements in embedded processors enable deployment of visual SLAM in low-cost, low-power, mass-market systems, but implementing SLAM on such platforms can be challenging. In this talk we explore the current state of visual SLAM algorithms and show how CEVA processors and software enable easy migration of SLAM algorithms from research to cost- and power-optimized production systems.
Deploying Visual SLAM in Low-power Devices
Session Speakers
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Ben Weiss
Computer Vision Expert, Customer Solution, CEVA
For the last 6 years Ben has been employed at CEVA as a computer vision expert and specializes in acceleration of vision algorithms over embedded devices. Prior to that, Ben worked in various positions in the aerospace industry focusing on communication and imaging systems. Mr. Weiss holds a BSc degree in Electrical and Computer Engineering from Ben-Gurion University.
