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- W2999403521 abstract "With the recent advancements in computer science and information technology, computers can now leverage human-like abilities in their operations. Image processing and computer vision technology made many practical applications easy and thus making our life comfortable with machine aid. Medical diagnosis and automatic car driving are two prominent examples in this field. Different types of human poses will be observed in our day to day life. The poses are distinguished from each other at the joints of body parts. In this paper we will discuss the methods to identify four fundamental human poses viz. sitting, standing, handshaking and waving. We are proposing here a framework which can automatically recognize the aforementioned four human poses in any angle or direction from the digital image. For working in this frame work we have created a image database of our own, which is described in subsequent chapter. Our working methodology involves image processing and neural network techniques. Finally, the performance of the proposed system is illustrated." @default.
- W2999403521 created "2020-01-23" @default.
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- W2999403521 date "2020-01-01" @default.
- W2999403521 modified "2023-09-27" @default.
- W2999403521 title "Human Pose Detection: A Machine Learning Approach" @default.
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- W2999403521 doi "https://doi.org/10.1007/978-3-030-37218-7_2" @default.
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