Vision4ce Develops AI-Based Video Tracking

By Mike Ball / 11 Nov 2019
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Vision4ce CHARM 100 embedded video tracking module

Vision4ce’s CHARM 100 embedded video tracking module

Vision4ce, a provider of rugged image and video processing solutions for unmanned systems, has developed true AI classification capabilities for its tracking products. The deep neural network-based classification application runs on Vision4ce’s embedded systems powered by NVIDIA’s Tegra architecture, and is ideal for any unmanned systems that require real-time video and image processing, tracking and classification detection technology.

Vision4ce’s deep neural network has been trained to localise and classify multiple objects on land, at sea and in the air, making it ideal for UAVs (unmanned aerial vehicles), UGVs (unmanned ground vehicles) and USVs (unmanned surface vehicles).

The system features the following capabilities:

  • Low Latency
  • Dual Processing Channels
  • Object Classification
  • Image Enhancement
  • Object Tracking
  • Sensor Fusion
  • Video Compression and Recording – H.264, M-JPEG
  • Electronic Image Stabilisation
  • Video Streaming – RTSP / MPEG-TS
  • Servo Platform Control
  • Camera Control
  • Panoramic Image Formation

With wide experience in real time video and image processing, Vision4ce can develop custom solutions for deployment on a wide range of unmanned systems. Their portfolio includes a line of GPU-based embedded platforms which are well-suited to AI edge computing.

The three videos below demonstrate Vision4ce’s deep neural network classification capabilities for air, land and sea targets:

Posted by Mike Ball Mike Ball is our resident technical editor here at Unmanned Systems Technology. Combining his passion for teaching, advanced engineering and all things unmanned, Mike keeps a watchful eye over everything related to the unmanned technical sector. With over 10 years’ experience in the unmanned field and a degree in engineering, Mike’s been heading up our technical team here for the last 8 years. Connect & Contact
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