V-Nova is promoting the use of MPEG-5 LCEVC in security camera platforms to optimize bandwidth and compute resources. The technology allows for the separation of base-layer video for AI analytics from enhancement layers for full-resolution viewing, aiming to improve stream density and reduce power consumption.
The immediate implication is a significant reduction in the hardware requirements for edge-based AI, as analytics engines can process lower-resolution base layers without full-frame decoding. This shift addresses the growing resource pressure on security platforms that must balance high-resolution archival needs with real-time inference. Within the broader ecosystem, the ability to layer LCEVC over existing codecs like HEVC and AV1 provides a scalable path for manufacturers to upgrade performance without replacing entire legacy infrastructures. Watch for whether major SoC manufacturers integrate these dual-layer decoding capabilities into their next-generation silicon to support higher camera densities per chip.
V-Nova has demonstrated that MPEG-5 LCEVC increases security camera stream density by 2.3x. By utilizing a base-layer for AI analytics and an enhancement layer for full-resolution video, the technology significantly reduces compute loads. This innovation allows manufacturers to improve performance and handle higher camera densities without replacing existing legacy hardware infrastructures.
According to V-Nova, MPEG-5 LCEVC increases stream density for 4Kp60 video by approximately 2.3x on illustrative AV1-based camera-SoC models.
Joint research with Intel shows that LCEVC provides 3.4x higher throughput and 70% lower power consumption for AI inference pipelines by allowing analytics engines to process lower-resolution base layers.
Yes, LCEVC can be layered over existing codecs such as AVC, HEVC, and AV1, providing a scalable path for manufacturers to upgrade performance.
When used with the AVC codec, LCEVC delivers average bitrate savings of 28% for HD video and 46% for UHD video.
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