Tag: computer vision

In previous blog posts, we have demonstrated using neural networks to do things such as object recognition and digit recognition. In this post, we will demonstrate a more practical example of vision, AI and machine learning running on PowerVR GPUs. This demo is showing how we can utilise the processing power of hardware such as the GPU to take input … Continued

These days we seem to take it for granted how powerful and sophisticated computers have become. We can talk to our phones and our Bluetooth speakers and they will respond with context-aware information; in certain cars you can take your hands off the wheel and let yourself be carried down the road by electronics, and we can share messages and … Continued

You may already have seen that Imagination has announced that its PowerVR GPUs are the first to achieve conformance with the OpenVX 1.1 specification from the Khronos™ Group. OpenVX is an open, royalty-free standard API for cross-platform acceleration of computer vision applications. By being ahead of the game, we at Imagination are demonstrating our commitment to ensuring that our hardware … Continued

It was clear last week at the annual Embedded Vision Summit in Santa Clara that the time of computer vision and deep learning on mobile had finally arrived. Interest in the area is growing noticeably – the Summit program expanded from one to two days this year, there were an impressive number of attendees, and the Technology Showcase was busy … Continued

About a month before CES 2015 I wrote an in-depth blog article about our PowerVR Series7XT GPUs, presenting the industry-leading performance efficiency gains made since Series6XT and giving an overview of their desktop-class features. Today I’m very excited to announce GT7200 Plus and GT7400 Plus, two new GPUs that represent the next evolution of our Rogue architecture. These new graphics … Continued

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 and PowerVR GPU. The algorithm employs several optimizations to improve performance and accuracy. In particular, instead of searching each entire frame for faces, the detector limits its search to regions in which faces … Continued

Modern mobile application processors are highly heterogeneous, combing a variety of different hardware components optimized for different tasks. As shown in the figure below, a processor designed for vision might include an Image Signal Processor (ISP) for acquiring image sensor data, a vector processor such as a GPU for efficient data-parallel operation on pixels and feature vectors, and a CPU … Continued

Computer vision is the use of computers to extract useful meaning from images, such as those that arise from photographs, video and real-time camera feeds. Thanks to the proliferation of low-power parallel processors, the increasing availability of 3D sensors and an active ecosystem of algorithm developers, it is now possible for many embedded devices to analyse their environments on-demand or … Continued

Heterogeneous architectures in embedded computing are fast becoming a reality – we indeed see many leading IP and semiconductor companies today building heterogeneous computing hardware. In the article below, I’m going to describe one typical use case for heterogeneous computing and the challenges that result from moving to a heterogeneous programming model. Running a beautification algorithm on a modern SoC … Continued