Many people love our analytics, but few truly understand them. Most misconceptions spur from a misunderstanding of how VideoIQ analytics function versus the numerous advanced motion detection alternatives. To truly comprehend the differences, we must first examine the basics. Thus, I have saved our analytics intricate self-learning capabilities for a later post, while we explore the fundamental elements of both technologies.
Advanced motion detection based systems rely mostly on pixel change analysis, sometimes complemented with simple algorithms. To put it simply, each camera has a field of view with (usually) a consistent background. When a certain number of pixels deviate from the norm, an alarm is triggered. On a calm, sunny day, such an approach can be quite effective, however, this can quickly become troublesome in challenging conditions. When a tree is shaking in the wind or snow is falling, many pixels are changing at once, often resulting in false alarms. Furthermore, the camera cannot determine a static background and detection begins to break down as it struggles to determine what’s deviating from the background and what is the background.