Category: Tech

What is VMS

VMS stands for video management software and is an essential part of any surveillance system. VMS software allows you to manage camera and recording settings, view multiple camera feeds, and set alerts for tampering and motion detection.

Video management software can also review and analyze your recorded video, giving you important information. These analytics can range from retail software that tracks customer movements to better design stores to motion detection searches for suspicious people who came on your property during the night.

Advanced Software Features

Learn about the software features and applications that help make your system run smoother. These include ways to quickly search through the recorded files you have to save time, and what types of software will work well with other cameras and NVRs.

License plate recognition, sometimes shortened to LPR, is a feature on some software that can detect, read, and store video of a car’s license plate. Used primarily in traffic monitoring in parking lots and gated security entrances, this allows the camera to capture a license plate number which is then compared to a database.

License Plate Recognition

How LPR Works

License plate recognition works when your camera captures video of a vehicle’s license plate and then either stores it for later review or runs the image through video analytics software to compare it to a database of stored license plate numbers.

If your database finds a match, your system can be set up to send you alerts. These alerts can be sent to your email or mobile phone, allowing you to know instantly, from anywhere, if your system finds something.

For license plate recognition to work, your camera needs a few specific things:

  • The angle of the camera is extremely important, because a camera that’s installed too high cannot see the license plate
  • The distance from the camera to the car must also be considered – while a camera may be able to zoom in quite a distance, you want to minimize the distance between camera and car
  • Lighting is also important – whether you install lights or use the camera’s built-in IR, you will need additional lighting at night
  • The speed of oncoming traffic must be low enough that the camera has enough time to focus on the license plate, often times no more than 35 mph depending on the angle, distance, and lighting

In addition, you’ll need to pay attention to the quality of the image. To be used as legal evidence, your video may need to meet standards set by your local law enforcement; one requirement might be that the captured license plate image be at least 15 pixels tall, to ensure clarity. A pixel counter, a feature included on some cameras, will help you meet these requirements.

How License Plate Recognition Can Help You

Situations that call for license plate capture may be very specific, but this feature is incredible important if you need to:

  • Secure an area, such as a military base or research facility
  • Monitor gated entrances & parking lot traffic
  • Track a known suspect’s vehicle
  • Find a stolen vehicle or car involved in a crime
  • Enforce parking laws, including time limits or reserved spaces

A popular application is access control for parking structures. A camera is placed at the entrance gate, and will automatically record an approaching car’s license plate to compare it to a database of approved visitors. If that license plate is on the database, the gate will open and allow the car to enter.

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Ambarella’s CV25 Camera System-on-Chip

Delivers advanced AI features at the edge in home security, professional surveillance cameras

SANTA CLARA, Calif.–Jan 7, 2019– Ambarella, Inc. (NASDAQ: AMBA) a leading developer of high-resolution video processing and computer vision semiconductors, today introduced the CV25 camera System-on-Chip (SoC), the latest in the CVflow family, combining advanced image processing, high-resolution video encoding and CVflow computer vision processing in a single, extremely low power design. The CV25’s CVflow architecture provides the Deep Neural Network (DNN) processing required for the next generation of affordable and intelligent home monitoring, professional surveillance, and aftermarket automotive solutions, including smart dash-cameras, Driver Monitoring Systems (DMS), and electronic mirrors.

“CV25 brings computer vision at the edge into the mainstream,” said Fermi Wang, President and CEO of Ambarella. “With this new SoC, we are sharply focused on reducing our customer’s overall system cost for delivery of significant computer vision performance, high-quality image processing and advanced cyber-security features at very low power. CV25-based cameras are capable of performing Artificial Intelligence (AI) at the edge, allowing features like facial recognition to happen in real-time on the device, rather than in the cloud.”

AI applications enabled at the edge include person recognition and the ability to distinguish between pets, persons, and vehicles. In smart video doorbells, CV25 can automatically recognize familiar faces approaching the front door, flag unknown persons, and alert the homeowner when a package is delivered. In driver monitoring systems, it can detect a driver’s drowsiness or level of distraction by monitoring their eyes and facial expressions.

CV25 delivers efficient video encoding in both AVC and HEVC formats with very low bitrates to minimize cloud storage costs. A high-performance Image Signal Processor (ISP) delivers outstanding imaging in low light conditions, and High Dynamic Range (HDR) processing extracts maximum image detail in high-contrast scenes. It includes a full suite of advanced cyber-security features to protect against hacking including secure boot, TrustZoneT, and I/O virtualization. Based on 10nm ultra-low power process technology, the CV25 chip is optimized for wire-free camera applications that require long battery life and small form factors.

As part of the CVflow family, the CV25 chip shares a common SDK, Computer Vision (CV) tools, ISP, and cyber-security features with the existing CV22 and CV2 SoCs, allowing multiple price-performance options. Ambarella’s complete set of CV tools helps customers easily port their own neural networks onto CV25. The set includes a compiler, debugger, and support for industry-standard machine learning frameworks such as CaffeT and TensorFlowT, with extensive guidelines for Convolutional Neural Networks (CNN) performance optimizations.

CV25 SoC Key Features:

  • CVflow architecture with CNN/deep learning support
  • 4Kp30 AVC and HEVC encoding with multi-stream support
  • Quad-core 1 GHz Arm®Cortex®-A53 processor with NEON DSP extensions and FPU
  • Advanced security features including OTP for secure boot, Trust Zone, and IO virtualization
  • Real-time hardware-accelerated 360-degree dewarping and Lens Distortion Correction (LDC)
  • Multi-channel ISP with up to 480 MPixels/s input pixel rate
  • Multi-exposure HDR and Wide Dynamic Range (WDR) processing, with LED flicker mitigation
  • SmartAVCT and SmartHEVCT intelligent rate control for lowest bitrates in security applications
  • Triple-sensor video input with high-speed SLVS/MIPI CSI-2/LVCMOS interfaces
  • Rich set of interfaces includes Gigabit Ethernet, USB 2.0 host and device, dual SD card controllers with SDXC support, HDMI v2.0, and MIPI DSI/CSI-2 output
  • Support for DDR4/LPDDR4/LPDDR4x
  • 10nm process technology
  • 13x13mm 0.65-pitch BGA  

CV25 will be demonstrated during CES 2019. To book an appointment for a demonstration, please contact Ambarella.