Machine Learning's Transformative Role in Human Activity Recognition Analysis
- Title
- Machine Learning's Transformative Role in Human Activity Recognition Analysis
- Creator
- Darshan R.; Janmitha S.N.; Deekshith S.; Kulkarni P.; Rajesh T.M.; Gurudas V.R.
- Description
- Human action recognition (HAR) is a burgeoning field of computer vision that seeks to automatically understand and classify the intricate movements performed by humans. From the graceful leaps of a ballerina to the decisive strides of a surgeon, HAR aims to decipher the language of motion, unlocking a plethora of potential applications. This abstract delves into the core of HAR, highlighting its key challenges and promising avenues for advancement. We begin by outlining the various modalities used for action recognition, such as RGB videos, depth sensors, and skeletal data, each offering unique perspectives on the human form. Next, we delve into the diverse set of algorithms employed for HAR, ranging from traditional machine learning techniques to the burgeoning realm of deep learning. We explore the strengths and limitations of each approach, emphasizing the crucial role of feature extraction and model selection in achieving accurate recognition. Challenges in Human Action Recognition (HAR), such as intra-class variations, inter-class similarities, and environmental factors. Ongoing efforts include robust feature development and contextual integration. The paper envisions HAR's future impact on healthcare, robotics, video surveillance, and augmented reality, presenting an invitation to explore the transformative world of human action recognition and its potential to enhance our interaction with technology. 2024 IEEE.
- Source
- Proceedings of InC4 2024 - 2024 IEEE International Conference on Contemporary Computing and Communications
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Activity Recognition; Artificial In telligence (AI); Computer Vision; Deep Learning; Human-Computer Interaction (HCI); Machine Learning; Motion Analysis; Pattern Recognition; Video Surveillance
- Coverage
- Darshan R., Dayananda Sagar university, Department of CSE, Bengaluru, India; Janmitha S.N., Dayananda Sagar university, Department of CSE, Bengaluru, India; Deekshith S., Dayananda Sagar university, Department of CSE, Bengaluru, India; Kulkarni P., Dayananda Sagar university, Department of CSE, Bengaluru, India; Rajesh T.M., Dayananda Sagar university, Department of CSE, Bengaluru, India; Gurudas V.R., CHRIST University, Department of CSE, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835038365-2
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Darshan R.; Janmitha S.N.; Deekshith S.; Kulkarni P.; Rajesh T.M.; Gurudas V.R., “Machine Learning's Transformative Role in Human Activity Recognition Analysis,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19247.