Results 221 to 230 of about 339,041 (256)

Chaotic Invariants for Human Action Recognition

2007 IEEE 11th International Conference on Computer Vision, 2007
The paper introduces an action recognition framework that uses concepts from the theory of chaotic systems to model and analyze nonlinear dynamics of human actions. Trajectories of reference joints are used as the representation of the non-linear dynamical system that is generating the action.
Ali, Saad, Basharat, Arslan, Shah, Mubarak   +2 more
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Human Action Recognition for Social Robots

2019 22nd International Conference on Control Systems and Computer Science (CSCS), 2019
Social assistive robotics is at the forefront of the effort for ensuring independent living and inclusion, especially for the elderly and vulnerable members of the population. We consider that to be proactive is a core requirement of such robotic systems. One key aspect of being proactive is to understand what the user is doing. We explored the task of
Mihai Nan, Alexandra Stefania Ghita, Alexandru-Florin Gavril, Mihai Trascau, Alexandru Sorici, Bogdan Cramariuc, Adina Magda Florea   +6 more
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Human action recognition in smart classroom

Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition, 2003
This paper presents a new system for teachers' natural complex action recognition in the smart classroom in order to realize an intelligent cameraman and virtual mouse. First, the system proposes a hybrid human model and employs a 2-order B-spline function to detect the two shoulder joints in the silhouette image to obtain the basic motion features ...
Haibing Ren, Guangyou Xu
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Biological inspired human action recognition

2013 IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS), 2013
Computational neuroscience studies through Functional magnetic resonance imaging (fMRI) claimed that human action recognition in the brain of mammalian pursues two separated pathways in the model, which are specialized for the analysis of motion (optic flow) and form information[3].
Bardia Yousefi, Chu Kiong Loo, Ali Memariani   +2 more
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Active classification for human action recognition

2013 IEEE International Conference on Image Processing, 2013
In this paper, we propose a novel classification method involving two processing steps. Given a test sample, the training data residing to its neighborhood are determined. Classification is performed by a Single-hidden Layer Feedforward Neural network exploiting labeling information of the training data appearing in the test sample neighborhood and ...
Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas   +2 more
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Tangent bundle for human action recognition

Face and Gesture 2011, 2011
Common human actions are instantly recognizable by people and increasingly machines need to understand this language if they are to engage smoothly with people. Here we introduce a new method for automated human action recognition. The proposed method represents videos as a tangent bundle on a Grassmann manifold.
Yui Man Lui, J. Ross Beveridge
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Human Action Recognition with Attribute Regularization

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance, 2012
Recently, attributes have been introduced to help object classification. Multi-task learning is an effective methodology to achieve this goal, which shares low-level features between attribute and object classifiers. Yet such a method neglects the constraints that attributes impose on classes which may fail to constrain the semantic relationship ...
Zhong Zhang 0001, Chunheng Wang, Baihua Xiao, Wen Zhou 0002, Shuang Liu 0001   +4 more
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A Review of Human Action Recognition in Video

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS), 2018
Human action recognition has a strong theoretical significance and wide application prospect in the field of video surveillance, human-computer interaction, virtual reality, etc. In this paper we analyze the present research situation from the datasets, action feature extraction, action recognition and classification.
Nenghuan Zhang, Yongbin Wang, Peng Yu
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Human Action Recognition for Disaster Detection

2020 29th International Conference on Computer Communications and Networks (ICCCN), 2020
In this paper, in case of a panic condition in public indoor space due to fire, earthquake, terror, etc., we propose a disaster detection system that detects disaster quickly by analyzing people's behavior using deep learning model. Four types of human behavior were collected as acceleration sensor data: walking, running, going to eat after class, and ...
Yull Kyu Han, Young Bok Choi
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PoHMM-based human action recognition

2009 10th Workshop on Image Analysis for Multimedia Interactive Services, 2009
In this paper we approach the human action recognition task using the Product of Hidden Markov Models (PoHMM). This approach allow us to get large state-space models from the normalized product of several simple HMMs. We compare this mixed graphical model with other directed multi-chain models like Coupled Hidden Markov Model (CHMM) or Factorial Hidden
Maria Ángeles Mendoza, Nicolas Pérez de la Blanca, Manuel J. Marín-Jiménez   +2 more
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