Nighttime learning method based on multiple stimuli
A learning method and multi-stimulation technology, applied in the field of learning tools, can solve the problems of resistance, easy sleepiness, and students' discomfort, and achieve the effect of improving the detection speed, reducing the search area, and improving the detection efficiency.
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Embodiment 1
[0082] combine figure 1 and figure 2 , a nighttime learning method based on multiple stimuli, including a learning system, the learning system includes an image acquisition unit for monitoring the students and an intervention unit for intervening on the fatigue of the students, and the image acquisition unit and the intervention unit are connected by communication to the main control unit;
[0083] The image acquisition unit includes a face acquisition module, an eye acquisition module and a mouth acquisition module;
[0084] The intervention unit includes a spray module, a blue light module and a sound module;
[0085] The main control unit includes an analysis module and a control module; the control module judges the fatigue degree of the trainee according to the analysis result of the analysis module, and the control module sends a signal to the intervention unit according to the result of the judgment, and through the intervention The unit wakes up the students;
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Embodiment 2
[0100] On the basis of Embodiment 1, when the analysis module analyzes the information collected by the face acquisition module, on the basis of the Rein-Lien Hsu algorithm, it analyzes the skin color distribution of the face in a single image, according to The skin color distribution characteristics of each image are used to segment the area, automatically select similar areas as the skin color area, detect and locate the face, directly locating the human eye in the image often causes a relatively large error, and use the improved skin color detection algorithm to locate the person Face, first locate the face part, which can reduce the search range of the eyes, improve the detection speed of the eyes, introduce the skin color feature into the face detection algorithm, use the skin color feature to eliminate the influence of non-skin color as much as possible, and segment possible candidate faces area, in order to reduce the scope of the search eye, improve the efficiency of th...
Embodiment 3
[0108] On the basis of embodiment 2, when the analysis module analyzes the information collected by the face acquisition module, on the basis of the Rein-Lien Hsu algorithm, it analyzes the skin color distribution of the face in a single image, according to The skin color distribution characteristics of each image are used for regional segmentation, and similar areas are automatically selected as skin color areas to detect and locate human faces.
[0109] The detection algorithm steps of described human face skin color are as follows:
[0110] S1. Set the collected image format to YUV (4:2:2:), directly take the logarithm of the UV value of each pixel to form a two-dimensional histogram showing a certain peak shape, and introduce the parameter K to eliminate interference , and there is K=S / H, where S represents the shortest distance from the peak to the adjacent peak valley, and H represents the height of the peak;
[0111] S2. Detect each peak area in the two-dimensional his...
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