1.1 Law Enforcement and Security
Law enforcement and security are critical elements to maintaining the wellâbeing of individuals and the protection of property. Societies rely on law enforcement agencies to provide these elements. Imaging systems and computer vision are means to sense and interpret situations in a manner that can amplify the effectiveness of officers within these agencies. There are several common elements shared by computer vision law enforcement and security applications, such as the detection and identification of events of interest. On the other hand, there are also distinctions that separate a security application from law enforcement. For instance, prediction and prevention are important for security applications, while accuracy and evidence are essential for law enforcement. In many cases, modules and components of a security system serve as a front end of a law enforcement system. For example, to enforce certain traffic violations, it is necessary to detect and identify the occurrence of that event.
Consider the impact of moving vehicle violations and examples of benefits enabled by computer vision law enforcement systems. There is a strong relationship between excessive speed and traffic accidents. In the United States in 2012, speeding was a contributing factor in 30% of all fatal crashes (10,219 lives) [1]. The economic cost of speedingârelated crashes was estimated to be $52 billion in 2010 [2]. In an extensive review of international studies, automated speed enforcement was estimated to reduce injuryârelated crashes by 20â25% [3]. The most commonly monitored moving violations include speeding, running red lights or stop signs, wrongâway driving, and illegal turns. Most traffic law enforcement applications in roadway computer vision systems involve analyzing wellâdefined trajectories and speeds within those trajectories, which leads to clearly defined rules and detections. In some cases, the detections are binary, such as in red light enforcement (stopped or passed through). Other applications require increased accuracy and precision, such as detecting speed violations and applying a fine according to the estimated vehicle speed. There are other deployed applications where the violation involves less definitive criterion, such as reckless driving.
Several moving violations require observation into the passenger compartment of a vehicle. Failure to wear a seat belt and operating a handheld cell phone while driving are two common safetyârelated passenger compartment violations. Seat belt use in motor vehicles is the single most effective traffic safety device for preventing death and injury to persons involved in motor vehicle accidents. Cell phone usage alone accounts for roughly 18% of car accidents caused by distracted drivers [4]. In addition, the National Highway Traffic Safety Administration (NHTSA) describes other behaviors resulting in distracted driving, including occupants in the vehicle eating, drinking, smoking, adjusting radio, adjusting environmental controls, and reaching for an object in the car. The conventional approach to enforcement of passenger compartment violations has been through traffic stops by law enforcement officers. This approach faces many challenges such as safety, traffic disruption, significant personnel cost, and the difficulty of determining cell phone usage or seat belt usage at high speed. Imaging technology and computer vision can provide automated or semiautomated enforcement of these violations.
Security of individuals and property is another factor in the monitoring of transportation networks. Video cameras have been widely used for this purpose due to their low cost, ease of installation and maintenance, and ability to provide rich and direct visual information to operators. The use of video cameras enables centralized operations, making it possible for an operator to âcoexistâ at multiple locations. It is also possible to go back in time and review events of interest. Many additional benefits can be gained by applying computer vision technologies within a camera network. Consider that, traditionally, the output of security cameras has either been viewed and analyzed in realâtime by human operators, or archived for later use if certain events have occurred. The former is error prone and costly, while the latter has lost some critical capabilities such as prediction and prevention. In a mediumâsized city with several thousand roadway cameras, computer vision and video analytics allow a community to fully reap the benefits of analyzing this massive amount of information and highlighting critical events in realâtime or in later forensic analysis.
In certain security and public safety applications, very rapid analysis of large video databases can aid a critical life or death situation. An Amber Alert or a Child Abduction Emergency is an emergency alert system to promptly inform the public when a child has been abducted. It has been successfully implemented in several countries throughout the world. When sufficient information is available about the incident (e.g., description of captorâs vehicle, plate number, and color), a search can be conducted across large databases of video that have been acquired from highway, local road, traffic light, and stop sign monitoring, to track and find the child. Similar to Amber Alert and much more common is Silver Alert, which is a notification issued by local authorities when a senior citizen or mentally impaired person is missing. Statistics indicates that it is highly desirable that an Amberâ/Silver Alertârelated search is conducted in a very fast and efficient manner, as 75% of the abducted are murdered within the first 3 h. Consider a statement from the US West Virginia code on Amber Alert 15â3Aâ7:
Human analysis of video from thousands of camera could take many days, while computer vision methods have the potential to rapidly extract critical information. The speed can be scaled by the available computational power, which is rapidly advancing due to highâspeed servers and cloud computing.
Whether it is safety of individuals or security of property, recognition of a vehicle is a key component of a roadway security system. Vehicles traveling on the public roadways in most countries are required by law to carry a c...
