This article was originally published at Texas Instruments' website. It is reprinted here with the permission of Texas Instruments. Today, automotive manufacturers are introducing new vehicle control features to save fuel, add security and convenience, and above all make cars much safer to drive. These changes, designed to assist drivers and make vehicles more autonomous […]
Making Cars Safer Through Technology Innovation 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 +
This article was originally published at Imagination Technologies' website, where it is one of a series of articles. It is reprinted here with the permission of Imagination Technologies. In a previous article we described our PowerVR Imaging Framework, a set of extensions to the OpenCL and EGL APIs that enable efficient zero-copy sharing of memory
Supported Zero-copy Flows Inside the PowerVR Imaging Framework Read More +
This is a reprint of a Xilinx-published white paper which is also available here (1 MB PDF). Xilinx INT8 optimization provide the best performance and most power efficient computational techniques for deep learning inference. Xilinx's integrated DSP architecture can achieve 1.75X solution-level performance at INT8 deep learning operations than other FPGA DSP architectures. ABSTRACT The
Deep Learning with INT8 Optimization on Xilinx Devices Read More +
This article was originally published at Imagination Technologies' website, where it is one of a series of articles. It is reprinted here with the permission of Imagination Technologies. Writing and optimizing code for heterogeneous computing can be difficult, especially if you are starting from scratch. Imagination has set up a new page where developers can
The PowerVR Imaging Framework Camera Demo Read More +
This article was originally published at Imagination Technologies' website, where it is one of a series of articles. It is reprinted here with the permission of Imagination Technologies. Imagination’s R&D group has developed a face detection algorithm, which is based on a classifier cascade and is optimized to run on mobile devices comprising a CPU
Deep Dive: Implementing Computer Vision with PowerVR (Part 3: OpenCL Face Detection) Read More +
This article was originally published at PathPartner Technology's website. It is reprinted here with the permission of PathPartner Technology. If your realtime image processing applications such as a driver monitoring system are dependent on OpenCV, you have to develop an OpenCV build environment on the target board. This article will guide you through the steps
This column was originally published at Vision Systems Design's website. It is reprinted here with the permission of PennWell. For most of its history, computer vision was a topic of academic research, gaining its first sizable commercial success in factory automation applications, where it has become an essential technology. Nevertheless, vision has remained a niche
Computer Vision Evolves Towards Ubiquity Read More +
This article was originally published by Embedded Vision Alliance consultant Dave Tokic. It is reprinted here with Tokic's permission. How one non-profit is helping the poorest by enabling cutting edge image search and self-driving cars 1.2 billion people (22 percent) live in extreme poverty on less than $1.25 a day worldwide and about 50% of
Taking on Poverty with Jobs Created by Machine Learning and Computer Vision Read More +
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