Human_Recognition

RECOGNITION. DYPIU. Researh Internship. HUMAN ACTION.

OUR TEAM. Yash Tiwari 20200802239 Suprabhat Shaurya 20200802166.

TABLE OF CONTENT. Introduction ML Algo in Human Action Recognition AI Algo in Human Action Recognition Data Collection and Preprocessing Techniques Training and Testing of Models Applications Challenges & Future Scope.

INTRODUCTION. What is it? Human action recognition is the ability of a computer to identify and classify human actions from video data sources. Why is it important? Human action recognition has many practical applications, including surveillance, healthcare, and sports analysis. How does it work? Human action recognition works by using machine learning algorithms to analyze and interpret data from video sources..

MACHINE LEARNING ALGORITHMS FOR Human Action Recognition.

Support Vector. An algorithm that separates data points by creating a hyperplane that maximizes the margin between positive and negative examples..

Artificial Intelligence Algorithms for Human Action Recognition.

Convolutional Neural Networks. A type of neural network that processes images by sliding a filter across the input and extracting features. ..

Data Collection and Preprocessing Techniques.

Data Collection. Data can be collected from a variety of sources, including cameras and motion sensors..

TRAINING AND TESTING OF MODELS. Validation Testing.

APPLICATIONS OF HUMAN ACTION RECOGNITION USING AI/ML.

Surveillance and Security ?️. Human action recognition can be used to detect abnormal behavior and alert security personnel..

CHALLENGES AND FUTURE DIRECTIONS. DATA QUALITY The quality of data used in human action recognition can have a significant impact on the accuracy of results. DATA PRIVACY The use of human action recognition technology raises concerns about privacy and data collection. REAL-TIME PERFORMANCE Human action recognition systems must be able to operate in real-time in order to be useful in many applications..

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