Gait recognition is a new biometric technology, which aims to identify people by their walking posture. Compared with other biometric technologies, gait recognition has the advantages of non-contact, long-distance and not easy to camouflage. In the field of intelligent video surveillance, gait recognition has more advantages than image recognition.
Gait recognition technology has many advantages
Compared with fingerprint, face, palmprint, vein and other static biometrics, gait belongs to dynamic features, so the recognition process is more complex. In most cases, fingerprint, iris and face biometric recognition need a certain degree of human cooperation, and their recognition distance is relatively short.
It is reported that the long-distance iris recognition technology launched by iris recognition company, which is the leading technology in the market, can achieve a distance of 2-3 meters; at present, the upper limit of face recognition distance is about 20 meters, but this distance level is still unable to compare with gait recognition. At present, the industry’s leading gait recognition technology, in the ordinary environment, the recognition distance can reach 50 meters, in the 4K HD camera, the recognition distance can even reach 100 meters, and it is 360 degree full view recognition, no matter what direction people come from, it can be recognized.
At the same time, almost all recognition methods are interfered by occlusion, but gait has unique advantages. First, the recognition distance is relatively long, so it takes longer time to adjust and respond to new changes in real time, such as occlusion removal. In addition, gait recognition is based on the whole body information, which can achieve 360 ° full view recognition. Even if the light changes, or the clothes change, or even the face is completely covered, it doesn’t matter. It can still be recognized. Therefore, gait recognition is more flexible and efficient than other recognition methods.
In addition, gait recognition doesn’t need the active cooperation of the recognized person, and can recognize the target person in a natural state, which makes the user experience more friendly. More importantly, gait recognition has higher security than other biometrics.
In the process of walking, because “I” must participate, so it is not to say that I am imitating others or being imitated by others. In addition, gait recognition is based on human body characteristics and walking posture recognition, not only recognize walking posture, body characteristics also play an important role. Therefore, deliberately camouflage walking posture, can not “cheat” gait recognition system, can still be recognized.
It is also because everyone’s walking posture is difficult to camouflage, so in criminal investigation, some criminals with anti detection consciousness, even if they can cheat the face recognition system by means of makeup and occlusion, are also difficult to fool the gait recognition system by camouflage walking posture. Therefore, in the field of public security criminal investigation, gait recognition technology is playing a more and more important role with its unique application advantages.
Application scenarios of gait recognition technology
Gait recognition technology can quickly retrieve and identify people in massive videos through many information points, such as human gait characteristics, posture, height, etc., even if the person’s face is covered or his back is facing the camera. At present, this technology is widely used in the field of public security.
In the field of public security criminal investigation, using the height, posture, movement pattern and other characteristics of the target person, we can quickly search out the target or video segment which is highly similar to the sample from the mass video, so as to achieve the purpose of quickly identifying the suspect in the case of changing, cross scene and facial occlusion, which makes up for the blind spot of face recognition technology under the same conditions.
In the field of smart home, gait recognition can be well applied to smart home system, giving home appliances intelligent perception and providing more personalized services. For many users, the use of smart home system is to better care and care for the elderly, children and pets at home.
At present, in order to enhance the intelligent interaction with users, many smart home systems on the market use basic human detection sensors or face recognition perception module, but these two methods have certain limitations. Human sensors can’t intelligently distinguish the elderly, children or pets. Face recognition needs to emphasize cooperation, so it can’t work in night vision environment. The gait recognition is not sensitive to the light environment and does not need to cooperate, which can make up for these application defects and truly achieve personalized service.
With the development of gait recognition technology, the changes brought by the technology will be full of imagination. After face recognition, gait recognition is expected to re open up a “blue ocean” of biometric recognition technology. As an e-commerce platform in algorithms, Ti Ling AI algorithm market has been collecting the most advanced algorithm models in the AI industry chain. It has the scene based capabilities of voice technology, face recognition, image technology and gait recognition, including applications in smart home, retail, commercial real estate, manufacturing, education, finance, culture and entertainment industries.
It is the expectation of Ti Ling AI algorithm market that AI technology can be truly implemented, rich cashing scenarios can be generated, and market value can be improved. At present, the platform has formed an industrial ecological chain that gathers technology demanders, system integrators, industry solution providers, application developers and hardware module suppliers. Ti Ling AI algorithm market has been actively opening up the upstream and downstream of AI industry, promoting AI products and solutions to form a closed-loop transaction and achieve win-win results.
Editor in charge: CC