İnterpreting the human posture in human videos and pictures constitutes the most basic structure of human posture prediction. A system is created that decides what the movement is and what purpose it is made by evaluating pictures and videos. In this way, a structure has been created that determines and classifies human movements as an automatic system. A mechanism of motional meaning contained in the created system has been recognized in such away that the pattern is expressed. It is intended to take advantage of these components by taking instant information. A result was obtained by primarily inferring instant still images and eliminating time intervals that do not contain information range. A classification was made according to their accuracy. Based on the location coordinates of the images and videos, it was tried to determine how people might react in the neck stage. Thanks to the analysis performed through the joints with optical flow calculation, motion information was obtained and classifications and analyses expressing the power of motion were created. Motion information on the region determined in the image is determined by the detection of joints, revealing the power generated by movement. The created histograms provide ease of classification of motion. Based on the reliability of the descriptions, which include the concept of the time in a sequential way with the detection of joints, it was desired to create a sliding classification mechanism within the framework of these joints. As a result of this study, it was aimed to obtain a functional structure that can recognize and understand the autonomous movement of stationary or moving beings. An efficient structure has been created in terms of providing a useful and facilitating mechanism by solving the problems in estimation.


    Access

    Download


    Export, share and cite



    Title :

    Human posture prediction by deep learning



    Publication date :

    2021-01-01


    Remarks:

    782


    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    Posture Prediction and Force/Torque Analysis for Human Hands

    Pitarch, Esteban Pena / Yang, Jingzhou / Kim, Joo et al. | SAE Technical Papers | 2006


    Posture prediction and force/torque analysis for human hands

    Yang,J. / Pitarch,E.P. / Kim,J. et al. | Automotive engineering | 2006


    Automobile Occupant Posture Prediction for Use with Human Models

    Flannagan, Carol A. C. / Schneider, Lawrence W. / Reed, Matthew P. et al. | SAE Technical Papers | 1999


    Automobile occupant posture prediction for use with human models

    Reed,M.P. / Manary,M.A. / Falannagan,C.A. et al. | Automotive engineering | 1999


    Automobile Occupant Posture Prediction for Use with Human Models

    Reed, M. P. / Manary, M. A. / Flannagan, C. A. C. et al. | British Library Conference Proceedings | 1999