pFlux eliminates background noise and nuisance motion for efficient object and event detection. In the example to the left, the pFlux output, represented in the lower right (labeled FTSG), reduces foreground nuisance motion, isolating objects and motion associated with vehicles.
Nuisance motion caused by weather negatively affects machine and human-based video surveillance operations. From left to right in the example to the right is raw RGB video, the pFlux video analysis and an overlay of the analysis on the raw video. Human objects are clearly identified and isolated from ambient motion related to falling snow.
Light and reflection
Surveillance video with light and reflection can create distractions, obscure objects and confuse AI/ML models. To the left, pFlux isolates objects of interest (vehicles) effectively even as these objects move through glare and reflection.
The pFlux output supplements video content with spatial and temporal analysis that is compliant with PII/GDPR/CCPA privacy standards. The image to the right is a colorized output of pFlux, representing objects in motion (blue) differentiated from persistent objects (red).