How Improved Video Quality can Help Automate Surveillance
Security management in sensitive areas is quite a challenge for years. Advanced technologies help us curb crimes and untoward incidents though it is still premature to call all public places safe. In an organization, employee’s peace of mind is dependent on a secure environment. To promote safety, we have to detect and rectify the anomalies that lead to unexpected incidents. A robust video surveillance system helps us increase the safety by pinpointing the security irregularities.
Why we Need Automated Video SurveillanceAutomation boosts efficiency and we are thus witnessing a general tendency to automate almost every process. Video surveillance is not an exception. Video surveillance systems generate a large number of datasets mainly comprised of images. Manually monitoring them can be ineffective as they are subject to human limitations. Hence we need to tend towards reducing the human role to analyze these images with due attention. Automating video surveillance would allow us to move the human resource towards response operations. This increases the real-time effectiveness of both warning and response stages. Automated video surveillance comprises of three modules:
- Motion Detection: Captures any movement happening under the field of view of the camera
- Subject Identification: Scans every image captured. Classifies the movement caused by human beings and other non-human entities like animals, wind or falling trees
- Behavior Classification: Decides on flagging the movement occurred with suitable notification
How Improved Video Quality helps Surveillance AutomationAll the key areas mentioned above require a good quality video to analyze and act. But smart surveillance is still a challenge considering the functional aspects of the automation. Poor video quality delays the identification and makes the response more ineffective.
One common approach to handle this challenge is by increasing the number of cameras used. But an increase in camera nodes adds to the increased demand for dependent hardware, physical space, and resources needed. It can also result in complex scenarios which fall outside the skillset of the current workforce.Hence, the preferred approach to handle this is to improve the video quality. It offers better results while maintaining the same number of cameras required. The dependent hardware can be made to adapt by upgrading the processing power of the System on Modules used. Consider a case where your current surveillance system offers video quality of 1080p. When you want to extend its reach, you can do it by increasing the video quality to 4K i.e nearly four times that of 1080p. The 4K video allows you to pause and zoom into the minute details which were not fathomable by 1080p Full HD video. It reduces frames for subject identification and hence pulls down the vital response time.
Factors Influencing Video QualityWhen you are improving the video quality, you need to consider following factors:
- Image Resolution: Image resolution is the detail an image holds and is typically measured in pixels per inch (PPI).
- Low Light Capabilities: It is a routine where surveillance cameras need to operate in low or almost no light. Hence security cameras need to be equipped to capture video at low light.
- Wide Range of Light: Cameras with poor video quality cannot adapt to drastic light variations even when they have bright sunlight. The well-known instance is when the field of view has a front door through which sunlight enters. When someone walks in the door, the camera will be subject to bright sunlight. By the time it closes, the camera will struggle to capture the person's identity.