Real-time Video Analytics

NVIDIA DeepStream pipelines for live CCTV over RTSP, with YOLO detection and CLIP-based semantic video search at scale.

Computer VisionNVIDIA DeepStreamYOLOCLIPRTSPTensorRT

The problem

A wall of CCTV monitors is only as useful as the human watching it. Teams need live detection on many camera streams at once — and the ability to search footage by meaning ("person in red jacket near the entrance") instead of scrubbing hours of video.

What I built

A real-time analytics system for live camera feeds:

  • Multi-stream ingestion of CCTV over RTSP through NVIDIA DeepStream.
  • Detection with YOLO running on-GPU for low-latency object and event detection across many streams.
  • Semantic video search powered by CLIP embeddings, so footage is searchable by natural-language description.

Architecture

  • DeepStream handles decode → inference → tracking on the GPU, keeping throughput high across concurrent streams.
  • Detection models optimised with TensorRT for real-time performance.
  • CLIP embeddings indexed for fast semantic retrieval over recorded segments.

Outcome

Live monitoring that scales to many cameras, plus the ability to find moments in footage by describing them — turning passive recording into a queryable system.

What you get

If you have camera feeds and need real-time detection or searchable video, I can design the DeepStream pipeline, the detection models, and the semantic search layer.

Interested in this?

Let's build it for your team

I can adapt this solution to your use case — or build something new from scratch.