Method and device for detecting image information

Abstract

An embodiment of the invention discloses a method and a device for detecting image information, and relates to the field of technologies for processing images. The method includes determining human eye regions in various video frames in video segments with preset durations; respectively computing light stream information of various pixel points in the human eye regions in the various video frames in the video segments; respectively counting the quantities of the downwardly moving pixel points and the upwardly moving pixel points in the human eye regions of the various video frames in the video segments according to the computed light stream information; acquiring human eye state characteristics of the various video frames in the video segments according to counting results; detecting to determine whether blinking phenomena are available in the video segments or not according to the acquired human eye state characteristics. The light stream information of the various pixel points in the human eye regions in each video frame in the corresponding video segment corresponds to a front frame of the video frame. According to the scheme, the method and the device in the embodiment of the invention have the advantages that the human eye state characteristics of the video frames are acquired by the aid of the image information among the video frames, and are utilized when whether the blinking phenomena are available in the video segments or not is detected, and accordingly the blinking detection accuracy can be improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image information detection method and device. Background technique [0002] With the development of smart terminals, various new ways of human-computer interaction continue to emerge, for example, realizing human-computer interaction through voice recognition or motion recognition, and so on. Compared with speech recognition, action recognition is not affected by the surrounding sound environment and can adapt to various sound environment application scenarios. [0003] Blink recognition is a kind of action recognition. When detecting whether there is a blink phenomenon, the human eye state characteristics of each video frame in a certain length of video clip are generally obtained first. Among them, the human eye state characteristics are used to represent the human eye in the video frame. state, such as eye-opening movement state, eye-closing movement state, etc.,...

AI Technical Summary

Problems solved by technology

However, when the above method is used to obtain the state characteristics of the human eye, it is easily affected by factors such as the surrounding lighting conditions, the user's position, and the individual differences of the user's human eye, resulting in a large error in the detected key points of the human eye, which in turn makes the obtained The human eye state characteristics of each video frame cannot correctly reflect the change of human eye state between each video frame, resulting in low accuracy of blink detection

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