Abstract: The present disclosure discloses a multicolor barcode. The multicolor barcode includes a start region (1), a data region (2), and a check region (3). The start region (1), the data region (2), and the check region (3) are arranged in sequence. The start region (1) includes a start color block that indicates a start position of the multicolor barcode, the data region (2) includes a data color block that indicates encoded data of the multicolor barcode, and the check region (3) includes a check color block that indicates an end position of the multicolor barcode. The start color block includes a first color block and a second color block, the first color block is located at the start position, and the second color block is a white color block. The present disclosure further provides a color calibration method for a multicolor barcode, and a computer-readable storage medium.

Abstract: The present disclosure discloses a multicolor barcode. The multicolor barcode includes a start region (1), a data region (2), and a check region (3). The start region (1), the data region (2), and the check region (3) are arranged in sequence. The start region (1) includes a start color block that indicates a start position of the multicolor barcode, the data region (2) includes a data color block that indicates encoded data of the multicolor barcode, and the check region (3) includes a check color block that indicates an end position of the multicolor barcode. The start color block includes a first color block and a second color block, the first color block is located at the start position, and the second color block is a white color block. The present disclosure further provides a color calibration method for a multicolor barcode, and a computer-readable storage medium.

Abstract: The disclosure provides a language learning method including task feedback and image check. The task feedback includes playing, by a sound module according to a learning instruction, the vocal content of a word, and taking, by a user, an object image corresponding to the word through a camera module of a terminal device. The image check includes receiving, by a processor module, the object image; identifying the object image according to a preestablished identification model; acquiring an identification result and comparing the identification result with the word; judging whether the object image taken by the user is correct; and feeding back, by a display module or the sound module, a judgment result.

Abstract: The present invention discloses a living-body detection based anti-cheating online research method, device and system. The method comprises the following steps: a model establishment step of establishing an action recognition model base; an information acquisition step of acquiring action recognition information about a user, the action recognition information comprising a current feature vector of a human face; and a feature comparison step of comparing the action recognition information about the user to a verification feature vector in the action recognition model base, the verification being passed if a comparison result indicates consistency. In the present invention, human facial recognition is introduced to an online questionnaire research system to conduct living-body detection; by adding a user verification link in which a facial action is completed as prompted, combined with the living-body detection technique, the validity and authenticity of questionnaire sample data is improved.

Abstract: The present invention discloses a method, device and system for evaluating a product recommendation degree. The method comprises the following steps: S1: establishing a facial recognition model base for humans; S2: acquiring facial recognition information about a human and a product viewing duration, the facial recognition information comprising a current feature vector of a human face; and S3: obtaining recommendation degree data for a user according to the facial recognition information and the product viewing duration. In the present invention, by acquiring through a camera video images of a user in the process of contacting a product, and analyzing a facial emotion change state of the user by an image recognition technique, in conjunction with the duration of the user viewing the product, recommendation degree data of the product are correspondingly formed, so that a product recommendation degree research can be performed efficiently.