LETTER FROM THE EDITOR Dear Colleague, If you're creating systems that see, the Embedded Vision Summit is the place to be! Plan now to join us May 1-3, 2017 in Santa Clara as stakeholders from every corner of the world's embedded vision ecosystem gather to examine the latest advances in computer vision, machine learning, and […]
Embedded Vision Insights: January 3, 2017 Edition Read More +
Ben Chehebar, co-founder of Compology, delivers the presentation "Using Vision to Improve Waste Collection Efficiency" at the December 2016 Embedded Vision Alliance Member Meeting. Chehebar describes a novel vision-based solution that is dramatically improving the efficiency of trash collection.
“Using Vision to Improve Waste Collection Efficiency,” a Presentation from Compology Read More +
LETTER FROM THE EDITOR Dear Colleague, If you're creating systems that see, the Embedded Vision Summit is the place to be! Plan now to join us May 1-3, 2017 in Santa Clara as stakeholders from every corner of the world's embedded vision ecosystem gather to examine the latest advances in computer vision, machine learning, and
Embedded Vision Insights: December 13, 2016 Edition Read More +
Computers can learn a lot about a person from their face – even if they don’t uniquely identify that person. Assessments of age range, gender, ethnicity, gaze direction, attention span, emotional state and other attributes are all now possible at real-time speeds, via advanced algorithms running on cost-effective hardware. This article provides an overview of
Facial Analysis Delivers Diverse Vision Processing Capabilities Read More +
Before a still image or video stream can be analyzed, it must first be captured and transferred to the processing subsystem. Cameras, along with the interfaces that connect them to the remainder of the system, are therefore critical aspects of any computer vision design. This article provides an overview of camera interfaces, and discusses their
Camera Interfaces Evolve to Address Growing Vision Processing Needs Read More +
LETTER FROM THE EDITOR Dear Colleague, The Embedded Vision Summit is the most important industry event for innovators developing and deploying products using computer vision. Next year’s Summit will take place May 1-3, 2017 in Santa Clara, California. We are assembling the presentation program and have a limited number of presentation opportunities. We are looking
Embedded Vision Insights: November 29, 2016 Edition Read More +
FEATURED VIDEOS "Implementing Eye Tracking for Medical, Automotive and Headset Applications," a Presentation from Xilinx and EyeTech Digital Systems When humans communicate with each other, we get important cues from watching each other’s eyes. Similarly, machines can gain valuable information and new capabilities by detecting and tracking users’ gazes. Robust eye tracking was once limited
Embedded Vision Insights: November 8, 2016 Edition Read More +
FEATURED VIDEOS "Low-power Embedded Vision: A Face Tracker Case Study," a Presentation from Synopsys The ability to reliably detect and track individual objects or people has numerous applications, for example in the video-surveillance and home entertainment fields. While this has proven to be a challenging problem, recent years have brought higher performance solutions such as
Embedded Vision Insights: October 25, 2016 Edition Read More +
Nik Gagvani, President and General Manager of CheckVideo, delivers the presentation "Intelligent Video Surveillance: Are We There Yet?" at the September 2016 Embedded Vision Alliance Member Meeting. Gagvani provides an insider's perspective on vision-enabled video surveillance applications.
“Intelligent Video Surveillance: Are We There Yet?,” a Presentation from CheckVideo Read More +
Vivienne Sze, Assistant Professor at MIT, delivers the presentation "Energy-efficient Hardware for Embedded Vision and Deep Convolutional Neural Networks" at the September 2016 Embedded Vision Alliance Member Meeting. Sze describes the results of her team's recent research on optimized hardware for deep learning. Followup: per Professor Sze, "Slides available at: http://www.rle.mit.edu/eems/wp-content/uploads/2016/07/Sze-Energy-Efficient-Hardware-for-Embedded-Vision-and-Deep-Learning-CVPR-2016-EVW.pdf".
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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