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Practical AI and computer vision technology is being developed for systems that span virtually every application, and many of these application areas will experience huge growth rates. With trendsetting products demonstrating what is possible, system designers have discovered that the suppliers of computer vision technology have removed the barriers to building practical computer vision systems—unleashing a huge wave of innovation for new products and applications.
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“Harnessing Cloud Computer Vision In a Real-time Consumer Product,” a Presentation from Cocoon Cam
Pavan Kumar, Co-founder and CTO at Cocoon Cam, delivers the presentation "Harnessing Cloud Computer Vision In a Real-time Consumer Product," at the Embedded Vision Alliance's September 2018 Vision Industry and Technology Forum. Kumar explains how his successful start-up is using edge and cloud vision computing to bring amazing new capabilities to the previously stagnant product
“Embedded AI for Smart Cities and Retail in China,” a Presentation from Horizon Robotics
Yufeng Zhang, VP of Global Business at Horizon Robotics, presents the “Embedded AI for Smart Cities and Retail in China,” tutorial at the May 2018 Embedded Vision Summit. Over the past ten years, online shopping has changed the way we do business. Now, with the development of AI technology, we are seeing the beginning of
“Leveraging Cloud Computer Vision for a Real-time Consumer Product,” a Presentation from Cocoon Cam
Pavan Kumar, Co-founder and CTO at Cocoon Cam, presents the "Leveraging Cloud Computer Vision for a Real-time Consumer Product" tutorial at the May 2018 Embedded Vision Summit. The capabilities of cloud computing are expanding rapidly. At the same time, cloud computing costs are falling. This makes it increasingly attractive to implement computer vision in the
“Intelligent Consumer Robots Powering the Smart Home,” a Presentation from iRobot
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
“Understanding Automotive Radar: Present and Future,” a Presentation from NXP Semiconductors
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
“Architecting a Smart Home Monitoring System with Millions of Cameras,” a Presentation from Comcast
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
“The Role of the Cloud in Autonomous Vehicle Vision Processing: A View from the Edge,” a Presentation from NXP Semiconductors
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
“Understanding Real-World Imaging Challenges for ADAS and Autonomous Vision Systems – IEEE P2020,” a Presentation from Algolux
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
“Computer Vision Hardware Acceleration for Driver Assistance,” a Presentation from Bosch
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
“The Roomba 980: Computer Vision Meets Consumer Robotics,” a Presentation from iRobot
Mario Munich, Senior Vice President of Technology at iRobot, presents the “Roomba 980: Computer Vision Meets Consumer Robotics” tutorial at the May 2018 Embedded Vision Summit. In 2015, iRobot launched the Roomba 980, introducing intelligent visual navigation to its successful line of vacuum cleaning robots. The availability of affordable electro-mechanical components, powerful embedded microprocessors and
