Human activity recognition project abstract It will mainly be used for eldercare and healthcare as an assistive technology when ensemble with other technologies like Internet of Things (IoT). Students, engineers, and students have studied human activity recognition in every part of the world for a long time. The accuracy of human action recognition has important applications in robotics. Abstract- The Human Activity Recognition (HAR) system is a prominent research area that aims to develop intelligent algorithms and systems capable of automatically identifying and classifying human activities based on sensor data. In this project, we implement a deep learning-based computer vision algorithm for human activity recognition. This data offers valuable insights that enhance our understanding of how physical activities contribute to improved physical health and overall quality of life. This approach leverages the advantages of each design, leading to enhanced performance recognition for activities. Hence, this review Jun 12, 2023 · The study of human activities has always incite researchers. Basic activities like walking and clapping are the focus. HAR is linked to a variety of technology-dependent daily life systems, such as human–computer interaction systems, security surveillance model human activities and what type of activities they are interested in. Jan 1, 2019 · Human Activity Recognition (HAR) has been a challenging problem yet it needs to be solved. In this book chapter, we are use of a YOLOv7-based model for human action recognition. 03274: Human Activity Recognition Using Tools of Convolutional Neural Networks: A State of the Art Review, Data Sets, Challenges and Future Prospects Dec 8, 2023 · Human Activity Recognition (HAR) has been such a demanding problem that needs to be solved. Moreover, we provide a comprehensive analysis of the existing, publicly available human activity classification datasets and examine the requirements for an ideal human activity recognition dataset . Abstract Increasing number of videos are becoming available in today’s world. This paper explores advancements in Human Activity Recognition (HAR) using deep learning techniques, emphasizing applications in healthcare and smart systems. After performing exploratory data Abstract. A significant amount of work has been done on human activity recognition and researchers have leveraged dif-ferent approaches, such as wearable, object-tagged, and device-free, to recognize Abstract Human activity recognition is gaining importance, not only in the view of security and surveillance but also due to psychological interests in un-derstanding the behavioral patterns of humans. However, the challenging factors in real-world scenarios, such as insufficient lighting and rapid movements, inevitably degrade the performance of RGB cameras. The raw sensor data will undergo preprocessing through two distinct methods: topological data analysis and statistical feature extraction from segmented time series. The Machine Learning-based activity recognition uses Computer vision techniques like YoloV4 and DarkNet to recognize activities performed by humans. Human Activity Recognition using Image Processing in this project user have to upload any input video to model and model first it will detect and identify the human activity and posture and will Oct 20, 2022 · Human activity recognition (HAR) is a complex and multifaceted problem. 1 day ago · Abstract Managing novelty in perception-based human activity recognition (HAR) is critical in realistic settings to improve task performance over time and ensure solution generalization outside of prior seen samples. Abstract Human activity recognition (HAR) has emerged as a transformative field with widespread applications, leveraging diverse sensor modalities to accurately identify and classify human activities. We have used data available at University of California Machine Learning repository to recognize six human activities. In our project, we have created an Android application that recognizes the daily human activities and calculate the calories burnt in real time. The research community has reported numerous approaches to perform HAR. Jul 23, 2025 · Human Activity Recognition First, we need to import all the required libraries for this project; the libraries used are numpy for gpu and deep learning imutils and cv2 for real-time imagery processing. Abstract: Human Activity Recognition is a subject of great research today and has its applications in remote healthcare, activity tracking of the elderly or the disables, calories burnt tracking etc. Novelty manifests in HAR as unseen samples, activities, objects, environments, and sensor changes, among other ways. Several reviews and surveys on HAR have already been published, but due to the constantly growing literature, the status of HAR literature needed to be updated. Jun 24, 2021 · Abstract: The aim of this project was to accurately classify sensor input data from the MHEALTH dataset into one of a number of physical activity classes. Abstract We study how to utilize the mobility of an embodied agent to improve its ability to recognize human activities. Researchers' interest in human daily activities is seen from studies on human activity recognition (HAR). Consequently, there is a growing need for efficient methods to extract This project implements a real-time Human Activity Recognition (HAR) system using advanced deep learning techniques. We first captured labeled triaxial acceleration Mar 30, 2015 · Abstract and Figures Human Activity Recognition is one of the active research areas in computer vision for various contexts like security surveillance, healthcare and human computer interaction. Key steps involve tracking segmented objects across frames and comparing motion patterns to templates to identify activities through model Apr 24, 2025 · Each model independently predicts the activity, and the ensembles method merges these predictions, often using voting or averaging, to produce a more accurate and reliable final classification. Abstract—Human activity recognition has gained importance in recent years due to its applications in various fields such as health, security and surveillance, entertainment, and intelligent environments. These activities are Standing, Sitting, Laying, Walking, walking upstairs and Walking downstairs. In this work, we investigate the use of a single three-axis accelerometer and the Kolmogorov Abstract Human activity recognition (HAR) has emerged as a transformative field with widespread applications, leveraging diverse sensor modalities to accurately identify and classify human activities. Dive into the state-of-the-art of Human Activity Recognition (HAR) and discover real-life applications plus datasets to try out. To address these challenges, biologically inspired event cameras offer a promising solution to overcome the . Techniques considered are Naïve Bayes, Support Vector Machine, K-Nearest Neighbor, Logistic Regression, Stochastic Gradient Descent, Decision Tree, Decision Tree with entropy, Random Forest, Gradient Boosting Decision Tree, and NGBoost algorithm. Nov 4, 2025 · Abstract Human Activity Recognition (HAR) plays a critical role in numerous applications, including healthcare monitoring, fitness tracking, and smart environments. End-users of HAR methods cover a range of sectors, including health, self-care, amusement, safety and monitoring. The document discusses human activity recognition from video data using computer vision techniques. The system employs a Long-term Recurrent Convolutional Networks (LRCN) model to accurately classify various human activities from video inputs captured via a webcam. ABSTRACT Human action recognition is a fundamental research problem in computer vision. We use transfer learning to adapt the SlowFast network pre-trained on human activity Jul 27, 2024 · Abstract Human Activity Recognition (HAR) is a highly promising research area meant to automatically identify and interpret human behaviour using data received from sensors in various contexts. This paper provides a comprehensive review of HAR techniques, focusing on the integration of sensor-based, vision-based, and hybrid methodologies. See full list on cs230. Feb 27, 2025 · Abstract Human Activity Recognition (HAR) plays a critical role in fields such as healthcare, sports, and human-computer interaction. The main focus area of HAR is in healthcare, providing assisted living, especially to elderly people and physically disabled people. Human Activity Recognition (HAR) has wide applications in rehabilitation centres, geriatric care houses, orphanages, and public places with large crowds. To evaluate the performance of the model, the action recognition results of YOLOv7 were compared with those using CNN+LSTM, YOLOv5, and Aug 27, 2022 · Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains, and vision and sensor-based data enable cutting-edge technologies to detect, recognize, and monitor human activities. A comprehensive review of existing human activity classification Abstract This study aims to investigate the performance of Machine Learning (ML) techniques used in Human Activity Recognition (HAR). stanford. Along with HAR approaches, various surveys have revealed HAR trends in various environments and applications. ABSTRACT We know that human movement or activity recognition is growing relevance, not only in surveillance and security, but also due to diverse academics' interests in understanding human behavioural or movement patterns. Aug 5, 2019 · Sensor-based activity recognition seeks the profound high-level knowledge about human activities from multitudes of low-level sensor readings — Deep Learning for Sensor-based Activity Recognition: A Survey, 2018. However, it is impossible for a person to manually analyze all of the videos and extract useful information out of them. It describes recognizing activities at different levels from object locations to full activities. edu 3 days ago · Abstract Real-time human activity recognition (HAR) must balance accuracy and latency under device constraints. Existing HAR techniques include manual feature extraction, codebook-based methods, and deep learning, each with limitations. This project focuses on classifying human activities using data collected from accelerometer and gyroscope sensors on phones and watches. Abstract: Machine learning research is heavily focused on human activity detection since it has various applications in a variety of fields, including security, entertainment, ambient supported living, and health management and monitoring. The human actions are acquired from raw time-series signals using smartphones and wearable devices' integrated sensors. Apr 8, 2025 · Human Activity Recognition (HAR) primarily relied on traditional RGB cameras to achieve high-performance activity recognition. With the rapid development of the internet of things (IoT) and artificial intelligence (AI) technologies, human activity recognition (HAR) has been applied in a variety of domains such as security and surveillance, human-robot interaction, and entertainment. We present SERA-HAR, a residual temporal convolutional framework augmented by two lightweight attentions. In this paper, a total of thirty-two recent research papers on sensing technologies used in HAR are reviewed. Following the Feb 2, 2022 · Abstract page for arXiv paper 2202. This project report provides a thorough exploration of the key aspects involved in the design, implementation, and evaluation of a Human Activity Recognition system You can perform it at various abstract levels. The essential stages of HAR architecture are feature Jul 2, 2025 · Abstract Human Activity Recognition (HAR) is crucial in multiple fields. Humans are rst detected with Convolutional Neural Network for Human Activity Recognition in Tensorflow - aqibsaeed/Human-Activity-Recognition-using-CNN Oct 1, 2018 · Abstract and Figures Human Activity Recognition (HAR) is classifying activity of a person using responsive sensors that are affected from human movement. In this paper, we present various state-of-the-art methods and describe each of them by Human Activity Recognition refers to the process of using machine learning algorithms and sensor data from various devices to detect and categorize human activities such as walking, running, and cooking. It is an important area of research in ubiquitous computing, human behavior analysis, and human-computer interaction, and has applications in maintaining a healthy lifestyle, patient Abstract: Human Activity Recognition is one of the active research areas in computer vision for various contexts like security surveillance, healthcare and human computer interaction. Even though a number of surveys and review papers have been published, there is a lack of HAR overview papers focusing on Abstract This project depicts recognition of Human activities using data generated from user’s Smart phone. Hence, this review aims to Abstract Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains, and vision and sensor-based data enable cutting-edge technologies to detect, recognize, and monitor human activities. Traditional deep learning (DL) approaches, while effective, often require extensive parameter tuning and may lack interpretability. HAR can be done with the help of sensors, smartphones or images. This report is a study on various existing techniques that have been brought together to form a working pipeline to study human activity in social gatherings. Aug 19, 2024 · Abstract Advanced wearable sensor devices have enabled the recording of vast amounts of movement data from individuals regarding their physical activities. Historically, sensor data for activity recognition was challenging and expensive to collect, requiring custom hardware. We in-troduce the embodied human activity recognition problem, where an agent moves in a 3D environment to recognize the category of ongoing human activities. Feb 1, 2025 · Abstract Human Activity Recognition (HAR) covers methods for automatically identifying human activities from a stream of data. 5fvfil bxrilyyd qvl hv m9 suwvze asy26 tmlb aaudr1 rg9p3