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NVIDIA Jetson Xavier Multi-Camera AI Demo from RidgeRun

Updated: Dec 9, 2019

  • This demo from RidgeRun shows the capabilities of the Jetson Xavier by performing :

  • Multi-camera capture through FPD-LINK III with Virtual Channels support,

  • Display of each individual camera stream on a grid, 

  • Application of CUDA video processing filters, classification and detection inference, 

  • Video stabilization processing and video streaming through the network.

Please watch Jetson Xavier Multicamera + AI + Video Stabilization + CUDA Video Processing FIlters demo from RidgeRun


Demo components:

D3 Engineering-Nvidia-Xavier FPD-Link III interface card:

D3 Engineering-D3RCM-OV10640-953 Rugged Camera Module:

This demo captures from 8x D3RCM-OV10640-953 Rugged Camera Modules at 1280x1080 @30fps using a serialized FDP-LINK III interface and virtual channels on NVIDIA Jetson AGX Xavier platform. The 8 camera streams are downscaled to 480x480 resolution and displayed on a grid of 1920x960 resolution. Extra processing is applied to different camera streams,

Camera_1: No extra processing, just normal camera stream. Intended to be used as a point of comparison against the streams with CUDA video processing filters.

Camera_2: Sobel in X-axis CUDA video filter applied with GstCUDA plugin.

Camera_3: Border Enhancement CUDA video filter applied with GstCUDA plugin.

Camera_4: Grayscale CUDA video filter applied with GstCUDA plugin.

Camera_5: No extra processing, just normal camera stream. Intended to be used as a point of comparison against the stream with video stabilization processing.

Camera_6: Video stabilization processing applied with GstNvStabilize plugin.

Camera_7: This camera stream is processed by a classification Deep Learning AI network. InceptionV1 Classification Inference applied with GstInference plugin using GPU accelerated TensorFlow.

Camera_8: This camera stream is processed by a detection Deep Learning AI network. Particularly, TinyYoloV2 Detection Inference applied with GstInference plugin using GPU accelerated TensorFlow.

One individual camera stream selected by the user from the demo menu is streamed to the network using the GstWebRTC plugin and an OpenWebRTC application.

Demo setup, demo features in detail, demo code and performance profiling information are explained in this RidgeRun & D3 Engineering - Nvidia Partner Showcase : Jetson Xavier Multi-Camera AI Demo RidgeRun Developer Wiki.

Contact Us

Please visit our Main Website for the RidgeRun online store or Contact Us for pricing information of the engineering support, product and services. You can also send an email to support@ridgerun.com for a technical support, more information about the features, evaluation version (if available) or for a details about how to sponsor a new feature.


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