The ability to detect faces has been around for some time for real time CCTV systems. However, these systems out of reach for many as they are expensive and would need specialized implementation that would drive the cost up higher. Therefore, detecting faces from videos instead is a viable alternative because it instantly adds face detection ability to any CCTV system.
Detecting faces allows you to count, track movements by detecting unique faces. Face detection finds and tracks human faces within a video. Multiple faces can be detected and subsequently be tracked as they move around.
This will be useful to analyze human traffic within a mall, street or even a restaurant or café. It would be possible to identify and track movement of unique human faces. Therefore, it is possible to perform a headcount of human traffic within the video.
Beyond detecting faces, it is more possible to detect emotions. Emotion Detection is an extension of the Face Detection video search that returns analysis on multiple emotional attributes from the faces detected, for example happiness, sadness, fear, anger, etc.
Recognizing the emotion of a person or crowd over time based allows us to track the emotional highs and lows within a particular time-frame. It also allows us to track someone’s emotions at a specific point of time. Answering questions like, how did the crowd react when the President makes a particular point? With emotion detection, it can be applicable to gauge audience responses in scenarios like:
- Focus groups
- Group reactions
Emotion detection can form a very good baseline for the scenarios above.