Dynamic Vision Sensor Heat Maps for Video Encoding

The patent applies different encoding qualities to different regions of the video frame based on a heat map. Regions with high temporal activity (identified by the heat map) are encoded with higher quality to preserve object details, while regions with low activity are encoded with lower quality to reduce bandwidth. This local differentiation resolves the contradiction by maintaining recognition accuracy in critical areas while reducing overall bandwidth consumption.

The video frame is segmented into multiple regions based on temporal activity levels derived from the heat map. Each segment is then encoded independently with appropriate quality parameters. This segmentation allows the system to allocate bandwidth efficiently - preserving detail in regions containing moving objects while compressing static background areas, thus resolving the bandwidth vs. accuracy trade-off.

The patent dynamically adjusts encoding parameters based on real-time heat map data that reflects temporal activity in different frame regions. Rather than using static encoding settings, the system adapts the compression level and quality for each region according to its activity level. This dynamic approach maintains detection accuracy in active regions while reducing power consumption through aggressive compression in inactive regions.

The encoding parameters (such as quantization level, compression ratio, and quality settings) are changed based on the heat map information. Regions with high temporal activity receive encoding parameters that preserve detail, while regions with low activity receive parameters that maximize compression. This parameter adaptation resolves the contradiction by optimizing the balance between detection accuracy and power consumption on a region-by-region basis.