Baby abnormal behavior detection method based on condition generative adversarial network and SVM

Abstract

The invention discloses a baby abnormal behavior detection method based on a condition generative adversarial network and an SVM, and belongs to the technical field of video image processing and deeplearning. Whether baby behaviors are abnormal or not is judged by analyzing baby motion trajectories in videos, firstly, baby videos are obtained, the baby videos are cut with reasonable length and converted into frame images, and the four limbs and the whole body are marked so that a sample library can be built; then, the condition generative adversarial network is used for performing target tracking on the whole body and the four limbs of the baby; then, wavelet approximation waveform and wavelet power spectrum calculation is performed on the obtained target motion trajectory, obtained characteristics are classified through the SVM, and comprehensive judging is performed; motion trajectory detection is performed on information of the whole body and the four limbs of the baby, informationis more comprehensive compared with single limb detection, wavelet region and power spectrum combined training is adopted, the detection precision is improved, whether baby behaviors are abnormal ornot is detected, intervention is performed as soon as possible, and the method is of a great significance for preventing diseases such as baby brain paralysis.

Description

technical field [0001] The invention belongs to the technical field of video image processing and deep learning, and in particular relates to a method for detecting abnormal behavior of infants based on conditional generative confrontation network and SVM. Background technique [0002] Abnormal behaviors of infants mainly refer to that within five months of birth, there is no small and medium-speed movement in all directions with variable acceleration throughout the whole body, and other forms of movement suitable for age (such as midline movement of limbs, hand-knee touch) , visual search, fingers grabbing clothes, etc.) and the overall movement fluency is not good. Abnormal behaviors of infants correspond to brain damage, which may lead to cerebral palsy in severe cases. Since cerebral palsy is usually diagnosed after a child is one to two years old, it is very important to study the detection of abnormal behaviors in early infants and to intervene in time. practical sign...

AI Technical Summary

Problems solved by technology

The first method is to use a specific video recording method for infants, and use the whole body motion quality evaluation criteria to judge whether the behavior is abnormal. This method mainly relies on observation and has a certain degree of subjectivity.

The second method is to wear a sensor device for the baby to observe the parameters, but this wearable method itself will cause some interference to the baby's movement, resulting in inaccurate prediction results

The third method is to use the computer to extract the baby's movement characteristics for pattern recognition analysis. This method will not interfere with the baby's movement and is objective, but in the process of extracting movement characteristics and recognition, often only a limited number of body parts are used. There is no analysis of the overall movement of the whole body, so it has a certain specificity

[0004] Due to the defects of the above algorithm, it is difficult to achieve ideal results in practical applications, so it is necessary to improve

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