Google Pixel Visual Core is a Custom Designed Co-Processor for Smartphone Cameras

Google unveiled their latest Pixel 2 & Pixel 2 XL premium smartphones powered by Snapdragon 835 SoC earlier this month, and while they are expected to go on sale tomorrow, reviewers have got their hands on samples, and one of the key feature is the camera that takes really good photos and videos as reported here and there. You’d think the ISP and DSP inside Snapdragon 835 SoC would handle any sort of processing required to take photos. But apparently that was not enough, as Google decided to design their own custom co-processor – called Pixel Visual Core -, and integrated it into Pixel 2 phones. The co-processor features a Cortex A53 core, an LPDDR4 memory interface, PCIe interface and MIPI CSI interface, as well as an image processing unit (IPU) IO block with 8 IPU cores. Google explains the IPU block will allow 3rd party applications to leverage features like low latency HDR+ photography, where the camera takes photos …

Intel Introduces Movidius Myriad X Vision Processing Unit with Dedicated Neural Compute Engine

Intel has just announced the third generation of Movidius Video Processing Units (VPU) with Myriad X VPU, which the company claims is the world’s first SoC shipping with a dedicated Neural Compute Engine for accelerating deep learning inferences at the edge, and giving devices the ability to see, understand and react to their environments in real time. Movidius Myraid X VPU key features: Neural Compute Engine – Dedicated on-chip accelerator for deep neural networks delivering over 1 trillion operations per second of DNN inferencing performance (based on peak floating-point computational throughput). 16x programmable 128-bit VLIW Vector Processors (SHAVE cores) optimized for computer vision workloads. 16x configurable MIPI Lanes – Connect up to 8 HD resolution RGB cameras for up to 700 million pixels per second of image signal processing throughput. 20x vision hardware accelerators to perform tasks such as optical flow and stereo depth. On-chip Memory – 2.5 MB homogeneous memory with up to 450 GB per second of internal …

Google Releases Android O Developer Preview 2, Announces Android Go for Low-End Devices, TensorFlow Lite

After the first Android O developer preview released in March, Google has just released the second developer preview during Google I/O 2017, which on top of features like PiP (picture-in-picture), notifications channels, autofill, and others found in the first preview, adds notifications dots, a new Android TV home screen, smart text selection, and soon TensorFlow Lite. Google also introduced Android Go project optimized for devices with 512 to 1GB RAM. Notifications dots (aka Notification Badges) are small dots that show on the top right of app icons – in supported launchers – in case a notification is available. You can then long press the icon to check out the notifications for the app, and dismiss or act on notifications. The feature can be disabled in the settings. Android TV “O” also gets a new launcher that allegedly “makes it easy to find, preview, and watch content provided by apps”. The launcher is customizable as users can control the channels that …

GPU Accelerated Object Recognition on Raspberry Pi 3 & Raspberry Pi Zero

You’ve probably already seen one or more object recognition demos, where a system equipped with a camera detects the type of object using deep learning algorithms either locally or in the cloud. It’s for example used in autonomous cars to detect pedestrian, pets, other cars and so on. Kochi Nakamura and his team have developed software based on GoogleNet deep neural network with a a 1000-class image classification model running on Raspberry Pi Zero and Raspberry Pi 3 and leveraging the VideoCore IV GPU found in Broadcom BCM283x processor in order to detect objects faster than with the CPU, more exactly about 3 times faster than using the four Cortex A53 cores in RPi 3. They just connected a battery, a display, and the official Raspberry Pi camera to the Raspberry Pi boards to be able to recognize various objects and animals. The first demo is with Raspberry Pi Zero. Raspberry Pi Zero version pic.twitter.com/5ALlnvFEe8 — Koichi Nakamura (@9_ties) April …