Facial Recognition for Law Enforcement: A Look at Successful Cases
28 documented cases from around the world where police used facial recognition systems for crime investigation and event security.
It is estimated that there are already over 700 million CCTV cameras installed in cities worldwide, with 20 cities having over 10 cameras installed for every 1,000 residents. However, police departments are often hesitant to share information about their use of facial recognition technology and the outcomes obtained, resulting in a lack of public trust and acceptance of these systems.
Today, facial recognition technology enhances the productivity of day-to-day policing in cities through at least 5 main usage scenarios.
1 A record index of persons of interest is created and maintained for law enforcement purposes. The data is processed in a closed circuit, and all actions in the system are logged. Access to the record index is restricted to the authorized users only.
2 Crime footage is automatically processed at high speed to detect faces, with the video being processed 30 times faster than the playback speed. As an example, 8 minutes are needed to process 4 hours of video.
3 The faces captured by the CCTV are compared with criminal records to establish the identity of potential suspects. Additionally, the system can help identify individuals who were in the vicinity at the time of the incident and may have been involved in the crime.
4Real-time searches of suspects are conducted to identify their current location.
5 The system can also identify individuals who have been banned from entering certain facilities, such as stadiums. This allows guards to avoid personally inspecting every spectator.
China, Russia, UK and US lead in successful cases
1 In 2019, the New York Police Department (NYPD) used facial recognition technology to identify a suspect who had left two rice cookers in a subway station, causing a brief panic and the evacuation of the station.
2 In 2018, facial recognition technology was used to identify and arrest a Cameroon woman for impersonating a U.S. citizen in Washington. That was the third case of arrest for impersonation at Dulles International Airport in 40 days after the new biometric verification technology had been implemented.
3 In 2019, police in New York used facial recognition technology to identify and arrest a suspect in a rape case. The technology helped the police make an arrest in less than 24 hours.
4 In 2016, facial recognition technology was used to arrest a suspect in a sexual assault case of a minor in Scranton, Pennsylvania.
5 In 2017, facial recognition technology was used to identify and arrest a suspect in a kidnapping and sexual molestation of a minor case in Indiana after 18 years. The suspect was hiding under a different identity and was arrested in Oregon.
6 In 2020, facial recognition technology was used to identify and arrest a suspect in a murder case in Las Vegas.
7 In 2023, facial recognition technology was used to arrest the son of a Russia’s Foreign Intelligence Service general who was on the international wanted list for fraud and breach of trust. The man was put on the wanted list by Switzerland, where he resided, and was arrested in Moscow.
8 In 2020, facial recognition technology was used to identify and arrest a suspect in an attempted rape case in New York.
9 In 2022, facial recognition technology was used to arrest a suspect who had been wanted for murder since 2009. According to the police, the suspect committed a murder in 2009 in the Stavropol region of Russia and was arrested in 2022 in Moscow.
10 In 2020, police in Delhi used facial recognition technology to identify and arrest three criminals for police resistance and robbery in Delhi. That was the first crime solved with the use of facial recognition technology in Delhi.
11 In 2023, facial recognition technology was used to identify and arrest a suspect in a murder case in Tamil Nadu, India.
12 In 2022, facial recognition technology was used to identify and arrest a suspect in a gun theft case in Pleasant View, Tennessee. The criminal was later charged with charged with 29 counts of theft, burglary, vandalism, and felon in possession of a firearm.
13 In 2019, police in China used facial recognition technology to identify and arrest a suspect in several murder cases in Xiamen. She had been on the run for 20 years.
14 In 2019, facial recognition technology was used to identify and arrest a suspect in a robbery murder case in Chongqing, China. He had been on the run since 2002.
15 In 2020, police in Austria used facial recognition technology to identify and arrest a suspect in a fraud case in Austria. The criminal was extradited to the US where he was wanted for fraud. He had been on the run since 2005.
16 In 2019, police in China used facial recognition technology to identify and arrest a suspect in an economic crime in Nanchang. The suspect was identified in a crowd of 50,000 while attending a concert.
17 In 2022, facial recognition technology was used to identify and arrest a suspect in a murder and possession of a firearm by a convicted felon case in Miami.
18 In 2021, facial recognition technology was used to identify and arrest a rape suspect who had been on the wanted list since 2013. The crime took place in the Kaluga region of Russia, and the suspect was found in Moscow eight years later.
19 In 2019, police in China used facial recognition technology to identify and arrest a suspect in a murder case in Shanghai. The criminal murdered her boyfriend and had been on the run for 17 years before her arrest in Yunnan.
20 In 2018, facial recognition technology was used to identify and arrest an internationally wanted suspect in a murder case in Buenos Aires, Argentina. The criminal was wanted by the Czech authorities under an INTERPOL Red Notice and had been on the run for 10 years.
21 In 2014, facial recognition technology was used to identify and arrest a suspect in a child sex abuse case in Nepal. The criminal was on the run from the FBI for 14 years.
Some of the NtechLab’s cases
22 In 2019, police in Moscow used facial recognition technology to identify and arrest the man wanted for theft of a million-dollar painting from the Tretyakov gallery. The technology helped the police to make an arrest and return the painting within 24 hours of the crime.
23 In 2022, facial recognition technology was used to identify and arrest a murder suspect who was wanted since 2003 in Kazan, a Russian city.
24 In 2022, facial recognition technology was used to identify and arrest a person who was wanted for a murder case. The murder took place in the Novgorod region of Russia, and the accused murderer was found in Kaluga, a Russian city, 25 years later.
25 In 2018, during the World Cup in Russia, facial recognition technology was used to arrest a drug dealer from Peru. The criminal was on the international wanted list.
26 In 2021, facial recognition technology was used to identify and arrest a married couple was wanted for murder since 2004. The couple committed the crime in 2004 in the Moscow region, left the country, and came back to Russia in 2019.
27 In 2023, facial recognition technology was used to identify and arrest a woman wanted for murder in Irkutsk, a Russian city, since 1994. The arrest took place in Moscow.
28 In 2021, police in Moscow used facial recognition technology to arrest a fugitive who ran away from prison a month prior. The arrested man was in prison for murder.
Facial recognition systems offer two major advantages. Firstly, they deliver results within the first few weeks of installation. For example, NtechLab’s facial recognition system was recently tested in Penza — a city in Russia with the population of half a million. Within a few days, the police managed to solve three crimes, including a rape case. Secondly, facial recognition technology can serve as a warning. Several stores that employ our facial recognition system to prevent theft have put up signs indicating the use of this technology. Consequently, theft rates have dropped dramatically.
How many crimes are actually solved using facial recognition technology
Today, facial recognition technology is being used or approved for use in surveillance purposes by around 100 countries worldwide.
1 Since the launch of INTERPOL’s facial recognition system at the end of 2016, nearly 1,500 individuals, including terrorists, criminals, fugitives, persons of interest, and missing persons, have been identified.
2 South Wales police reported in 2018 that the introduction of facial recognition technology led to more than 450 arrests in one year. It also said no one had been arrested after an incorrect match.
3 In 2019, the NYPD received 9,850 requests for facial recognition comparison and identified 2,510 potential matches. The system flagged potential matches in 68 murder cases, 66 rape cases, 277 felony assault cases, 386 robbery cases, and 525 grand larceny cases.
4 Since its launch in September 2020, facial recognition system of the Moscow Metro has identified over 6,000 individuals wanted for various crimes.
5 Police in Singapore used facial recognition technology to solve over 6,000 various crimes.
Some more of the NtechLab’s cases
6 Since its introduction in 2017, Moscow’s facial recognition system has helped to detain over 7,700 individuals wanted for various crimes.
7 Since its introduction in June 2022, facial recognition system in Anapa, one of the most popular resorts in Russia, has led to the detention of over 100 individuals wanted for various crimes within a year.
8 Facial recognition technology was used by authorities during the 2018 FIFA World Cup in Russia to enhance security measures. The system identified over 180 individuals, including those banned from attending soccer games, wanted for various crimes, and even fugitives wanted in other countries.
Cities that have invested in technologies like facial recognition, silhouette recognition, and vehicle recognition can use these capabilities in other domains to further improve their operations. For instance, they can leverage these technologies for traffic intelligence to identify congested roads and recommend alternative routes, infrastructure condition monitoring for preventive maintenance, and flood or other natural disaster monitoring to enhance safety and locate missing people.
