As compared with other biological feature recognition technologies, a human face recognition technology has unique advantages in practical application: human face can be directly acquired via a camera, and the recognition procedure may be completed in a non-contacting manner conveniently and quickly.
Currently, human face recognition technology is already applied to many fields such as financing, education, scenic spots, travel and transport and social insurance. However, the human face recognition technology brings about convenience as well as some problems. For example, human face can be easily acquired so that human face can be duplicated by some people in a picture or video manner to achieve the purpose of stealing information. Particularly in the new financing industry, human face recognition technology is already gradually applied to remote account opening, money withdrawal, payment and so on, and involves users' interests.
To this end, a living body detection technology is proposed in the prior art. Plainly speaking, the so-called living body detection means detecting that the face corresponds to a “living person” during human face recognition.
Sources of non-living bodies are wide, and include photos and video displayed on a mobile phone or Pad, and printed photos on different materials (including curving, folding, clipping and hole-digging in various cases), and so on.
The living body detection is applied on important occasions such as social insurance and online account opening. For example, pension cannot be withdrawn unless an elderly user's identity is determined authentic and the elderly user is still alive through verification. Upon online account opening, this can ensure authenticity, validity and safety of the user information.
In a conventional living body detection manner, it is usual to use a single camera to acquire user pictures, perform feature extraction for the user pictures, and thereby determine whether the user is a living body according to the extracted features.
However, a detection result achieved in this manner has a lower accuracy, and a non-living body is probably mistaken as a living body.