Shulou(Shulou.com)06/02 Report--

In the past few weeks, three global high-tech companies (IBM, Microsoft and Amazon) have announced that they will not support the use of new facial recognition technology by police and other law enforcement agencies. In fact, when IBM announced the news, it was announced by its chief executive, highlighting the possibility that the technology could be compromised in terms of ethnic identity and human rights violations.

Recently, the United States introduced a bill in the Senate facial recognition and Biometric Technology suspension Act to ban the use of facial recognition technology by law enforcement agencies.

It is believed that face recognition technology is racially biased. When analyzing and identifying personal goals, technology can provide very accurate results for white individuals (male / female), but for blacks (mainly female), the effect is very low, so there is a problem of technological bias and related challenges. This may be due to the low availability of data sets and training models, which can be solved once the technology obtains a large amount of data and uses the correct algorithm.

Face recognition has three main components: computer vision, AI-based algorithm and database for training and verification. The camera captures the image and maps it to the data repository with the help of the algorithm to identify the target. It works primarily on the tagged feature set, which establishes correlation and data accumulation and aggregation. Parameters, such as the distance between eyes, nose, and face shapes, define more than 100 data points, which are defined on the data matrix.

Facial recognition is an important part of our daily life, which is a common unlocking function of our mobile phones. We see it at the airport for secure authentication and for access control in high-security places. Although there are other biometric scanning technologies, such as iris scanners and fingerprint scanners, these technologies are more useful for small-scale personal identification. Face recognition is used for large-scale and extensive crowd recognition.

In law enforcement agencies, the use of facial recognition is very common, mainly for large-scale surveillance, crowd management, personnel counting, etc., and is more common in smart city management.

According to Grand View Research, a global market research firm, the global face recognition market is worth $3.4 billion and is expected to grow by 14.5% CAGR in the next seven years. Based on technology, the facial recognition market is divided into 2D, 3D and facial analysis.

Face recognition technology has been widely used for large-scale personnel detection in Israel, Britain, Germany and other countries / regions, especially in the current novel coronavirus pandemic, many areas have launched larger-scale surveillance programs. For example, more than a large number of surveillance cameras with built-in face recognition technology and other video analysis applications have been deployed in the public areas of major cities.

There are also security and privacy issues for the data collected and stored. The events of data disclosure, cloning and adjustment have been fully verified by facts. At present, few regulations are configured to address these challenges. GDPR (General data Protection Regulation) is one of the regulations formulated by the European Union to solve privacy issues.

In addition to global high-tech companies, many camera OEM provide FR analytics as part of a bundled solution. Original equipment manufacturers from Asia occupy an important share of the global market. In addition, there are many professional video analysis companies that provide face recognition technology as independent solutions.

In India, the share of technology in effective regulation is growing. The police modernization programme was initially launched through the launch of the Crime and Crime tracking Network system (CCTNS), which is further reinforced by the Digital India Initiative, such as the Security and Smart City initiative.

According to the Police Research and Development Bureau of the Government of India, as of 1 January 2017, the police-to-population ratio was 193, while the United Nations recommended ratio of 220 (i.e. the number of police officers out of a population of 100000). This proportion has increased significantly from 142 in 2006 to 193 in early 2017. Technology can further bridge this gap and help the police maintain law and order and prevent and alleviate crime.

In big cities such as Mumbai, Delhi and Hyderabad, recent safe city plans include video analysis and facial recognition. Face recognition analysis and prediction is an important element of deploying solutions in these cities. This produced good results and helped the city solve major crimes quickly. The police leadership has accepted this technology, which can help them properly allocate and deploy manpower and carry out effective monitoring.

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