Sensors and Cameras

“Introduction to LiDAR for Machine Perception,” a Presentation from Deepen AI

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Mohammad Musa, the Founder and CEO of Deepen AI, presents the “Introduction to LiDAR for Machine Perception” tutorial at the May 2018 Embedded Vision Summit. LiDAR sensors use pulsed laser light to construct 3D representations of objects and terrain. Recently, interest in LiDAR has grown, for example for generating high-definition maps required for autonomous vehicles […]

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“Intelligent Consumer Robots Powering the Smart Home,” a Presentation from iRobot

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Mario Munich, Senior Vice President of Technology at iRobot, presents the “Intelligent Consumer Robots Powering the Smart Home” tutorial at the May 2018 Embedded Vision Summit. The Internet Of Things (IoT) has rapidly developed in the past few years, enabled by affordable electronics components and powerful embedded microprocessors, ubiquitous internet access and WiFi in the

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“Understanding Automotive Radar: Present and Future,” a Presentation from NXP Semiconductors

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Arunesh Roy, Radar Algorithms Architect at NXP Semiconductors, presents the “Understanding Automotive Radar: Present and Future” tutorial at the May 2018 Embedded Vision Summit. Thanks to its proven, all-weather range detection capability, radar is increasingly used for driver assistance functions such as automatic emergency braking and adaptive cruise control. Radar is considered a crucial sensing

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“Architecting a Smart Home Monitoring System with Millions of Cameras,” a Presentation from Comcast

Algorithms, Edge AI and Vision Alliance, Processors, Security, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

Hongcheng Wang, Senior Manager of Technical R&D at Comcast, presents the “Architecting a Smart Home Monitoring System with Millions of Cameras” tutorial at the May 2018 Embedded Vision Summit. Video monitoring is a critical capability for the smart home. With millions of cameras streaming to the cloud, efficient and scalable video analytics becomes essential. To

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“The Role of the Cloud in Autonomous Vehicle Vision Processing: A View from the Edge,” a Presentation from NXP Semiconductors

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Ali Osman Ors, Director of Automotive Microcontrollers and Processors at NXP Semiconductors, presents the “Role of the Cloud in Autonomous Vehicle Vision Processing: A View from the Edge” tutorial at the May 2018 Embedded Vision Summit. Regardless of the processing topology—distributed, centralized or hybrid —sensor processing in automotive is an edge compute problem. However, with

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“Understanding Real-World Imaging Challenges for ADAS and Autonomous Vision Systems – IEEE P2020,” a Presentation from Algolux

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Felix Heide, CTO and Co-founder of Algolux, presents the “Understanding Real-World Imaging Challenges for ADAS and Autonomous Vision Systems – IEEE P2020” tutorial at the May 2018 Embedded Vision Summit. ADAS and autonomous driving systems rely on sophisticated sensor, image processing and neural-network based perception technologies. This has resulted in effective driver assistance capabilities and

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“From 2D to 3D: How Depth Sensing Will Shape the Future of Vision,” a Presentation from Yole Développement

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Guillaume Girardin, Division Director for photonics, sensing and displays at Yole Développement, presents the “From 2D to 3D: How Depth Sensing Will Shape the Future of Vision” tutorial at the May 2018 Embedded Vision Summit. For several decades, 3D imaging and sensing technologies have matured, thanks to extensive, successful deployments in high-end applications, mainly in

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“Enabling Cross-platform Deep Learning Applications with the Intel CV SDK,” a Presentation from Intel

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Yury Gorbachev, Principal Engineer and the Lead Architect for the Computer Vision SDK at Intel, presents the “Enabling Cross-platform Deep Learning Applications with the Intel CV SDK” tutorial at the May 2018 Embedded Vision Summit. Intel offers a wide array of processors for computer vision and deep learning at the edge, including CPUs, GPUs, VPUs

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“Computer Vision Hardware Acceleration for Driver Assistance,” a Presentation from Bosch

Algorithms, Automotive, Edge AI and Vision Alliance, Processors, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

Markus Tremmel, Chief Expert for ADAS at Bosch, presents the “Computer Vision Hardware Acceleration for Driver Assistance” tutorial at the May 2018 Embedded Vision Summit. With highly automated and fully automated driver assistance system just around the corner, next generation ADAS sensors and central ECUs will have much higher safety and functional requirements to cope

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Computer Vision for Augmented Reality in Embedded Designs

Algorithms, Articles, Augmented Reality, Edge AI and Vision Alliance, NXP Semiconductors, Processors, Sensors and Cameras, Software, Synopsys, Technical Articles, Tools, videantis /

Augmented reality (AR) and related technologies and products are becoming increasingly popular and prevalent, led by their adoption in smartphones, tablets and other mobile computing and communications devices. While developers of more deeply embedded platforms are also motivated to incorporate AR capabilities in their products, the comparative scarcity of processing, memory, storage, and networking resources

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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