This article was originally published at Texas Instruments’ website (PDF). It is reprinted here with the permission of Texas Instruments. Introduction There were 1.2 million global traffic deaths in 20101. 93 percent of traffic accidents in the US are due to human error, typically due to inattention2. ADAS (Advanced Driver Assistance Systems) applications such as […]
TI Vision SDK, Optimized Vision Libraries for ADAS Systems Read More +
This article was originally published as a two-part blog series at Aldec's website. It is reprinted here with the permission of Aldec. It's pretty hard to overestimate the role of heterogeneous embedded systems based on Xilinx® Zynq®-7000 All-Programmable devices in tasks like computer vision. Many consumer electronics and specialized devices are emerging to facilitate and
Leveraging the Power of VDMA Engines for Computer Vision Apps with TySOM Read More +
This article was originally published at Texas Instruments’ website (PDF). It is reprinted here with the permission of Texas Instruments. Introduction Computer-vision algorithms used to be quite different from one another. For example, one algorithm would use Hough transforms to detect lines and circles, whereas detecting objects of interest in images would require another technique
Embedded Low-power Deep Learning with TIDL Read More +
Deep learning and other machine learning techniques have rapidly become a transformative force in computer vision. Compared to conventional computer vision techniques, machine learning algorithms deliver superior results on functions such as recognizing objects, localizing objects within a frame, and determining which pixels belong to which object. Even problems like optical flow and stereo correspondence,
Data Sets for Machine Learning Model Training Read More +
DNNs (deep neural networks) have transformed the field of computer vision, delivering superior results on functions such as recognizing objects, localizing objects within a frame, and determining which pixels belong to which object. Even problems like optical flow and stereo correspondence, which had been solved quite well with conventional techniques, are now finding even better
Implementing Vision with Deep Learning in Resource-constrained Designs Read More +
This article was originally published at Synopsys' website. It is reprinted here with the permission of Synopsys. Examples of applications abound where high-performance, low-power embedded vision processors are used: a mobile phone using face recognition to identify a user, an augmented or mixed reality headset identifying your hands and the layout of your living room
Implementing High-performance Deep Learning Without Breaking Your Power Budget Read More +
The ability to "stitch" together (offline or in real-time) multiple images taken simultaneously by multiple cameras and/or sequentially by a single camera, in both cases capturing varying viewpoints of a scene, is becoming an increasingly appealing (if not necessary) capability in an expanding variety of applications. High quality of results is a critical requirement, one
Computer Vision in Surround View Applications Read More +
This article was originally published at Lattice Semiconductor's website. It is reprinted here with the permission of Lattice Semiconductor. The rapid rise in the number of sensors that are being integrated into the current generation of embedded designs, as well as the integration of low cost cameras and displays, have opened the door to a
Solving Intelligence, Vision and Connectivity Challenges at the Edge with ECP5 FPGAs Read More +
This article was originally published by Dave Tokic of Alliance member company Algolux. It is reprinted here with Tokic's permission. To really reduce vehicle accidents and fatalities, the cameras in our cars need to “see” better… much better. This has been a major theme in the automotive industry that has become even more urgent as traffic
Seeing Clearer – Driving Toward Better Cameras for Safer Vehicles Read More +
This article was originally published at Basler's website. It is reprinted here with the permission of Basler. What do image processing systems have to do with keeping foodstuffs in good shape? Everyone prefers foodstuffs that are fresh and outwardly attractive. Image processing systems are frequently used during the quality assurance process for these products to
Fundamentals of Image Processing Systems Read More +
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.
1646 N. California Blvd.,
Suite 360
Walnut Creek, CA 94596 USA
