Developed by REBOTNIX. Intelligent image compression that reduces bandwidth and storage while preserving everything relevant for detection and analysis.
Standard compression algorithms treat all pixels equally. KINEVA Context Compression understands the image. It compresses background regions aggressively while retaining full detail in areas that carry information for AI models. The result: up to 90% smaller files with no loss in detection accuracy.
A lightweight saliency model scores every region of the image before compression. High-relevance regions are preserved at full quality. Low-relevance regions are compressed heavily. The output is a standard image file compatible with any downstream pipeline.
Runs on-device at full camera framerate. No cloud required.
Dramatically lower storage and bandwidth requirements without sacrificing the data your AI models depend on.
The model knows what matters. Regions used for detection are kept at full resolution. Accuracy stays identical.
Runs locally on REBOTNIX GUSTAV hardware. Real-time throughput, no latency added to the pipeline.
KINEVA Context Compression integrates into any existing camera pipeline. No model changes required.