scholarly journals Action Recognition Robust to Background Clutter by Using Stereo Vision

2012 ◽  
pp. 332-341 ◽  
Author(s):  
Jordi Sanchez-Riera ◽  
Jan Čech ◽  
Radu Horaud
Keyword(s):  
Action Recognition ◽  
Stereo Vision ◽  
Background Clutter

scholarly journals Semi-Supervised Image-to-Video Adaptation for Video Action Recognition

2021 ◽  
Vol 9 (VIII) ◽  
pp. 760-763
Author(s):  
Rohan Munshi
Keyword(s):  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action ◽  
Camera Motion ◽  
Video Adaptation ◽  
Surveillance Video ◽  
Systematic Classification ◽  
The Public ◽  
Background Clutter ◽  
Public Datasets

Given a sequence of images i.e. video, the task given a sequence of images i.e. video, the task of action recognition is to identify the most same action among the action sequences learned by the system. Such human action recognition is based on evidence gathered from videos. It has a lot of applications including surveillance, video indexing, biometrics, telehealth, and human-computer interaction. Vision-based human activity recognition is plagued by numerous challenges thanks to reading changes, occlusion, variation in execution rate, camera motion, and background clutter. In this survey, we provide an overview and report of the existing methods based on their ability to handle these challenges as well as how these methods can be generalized and their ability to detect abnormal actions. Such systematic classification can facilitate researchers to spot the acceptable ways on the market to deal with every one of the challenges visaged and their limitations. In addition to this, we also identify the public datasets and the challenges posed by them. From this survey, we have a tendency to draw conclusions relating to however well a challenge has been resolved, and that we determine potential analysis areas that need more work.

On the role of edge orientation in stereo vision

2019 ◽  
Vol 2019 (12) ◽  
pp. 209-1-209-6
Author(s):  
Alfredo Restrepo ◽  
Julian Quiroga
Keyword(s):  
Stereo Vision ◽  
Edge Orientation

Motion Estimation byUsing Stereo Vision Analysis For Underwater Observation System

2019 ◽  
Author(s):  
Masyhuri Husna Binti Mazlan ◽  
Morisawa Daisuke ◽  
Koike Yoshikazu ◽  
Shimizu Junji ◽  
Enomoto Eriko ◽  
...  
Keyword(s):  
Motion Estimation ◽  
Stereo Vision ◽  
Observation System ◽  
Underwater Observation

Human action recognition using simple geometric features and a finite state machine

2013 ◽  
Vol 18 (2-3) ◽  
pp. 49-60 ◽  
Author(s):  
Damian Dudzńiski ◽  
Tomasz Kryjak ◽  
Zbigniew Mikrut
Keyword(s):  
Action Recognition ◽  
Finite State Machine ◽  
Recognition Rate ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Stream ◽  
State Machine ◽  
Recognition Algorithm ◽  
Finite State ◽  
Correct Recognition Rate

Abstract In this paper a human action recognition algorithm, which uses background generation with shadow elimination, silhouette description based on simple geometrical features and a finite state machine for recognizing particular actions is described. The performed tests indicate that this approach obtains a 81 % correct recognition rate allowing real-time image processing of a 360 X 288 video stream.

Deep Learning for Human Action Recognition Survey

2018 ◽  
Vol 6 (10) ◽  
pp. 323-328
Author(s):  
K.Kiruba . ◽  
D. Shiloah Elizabeth ◽  
C Sunil Retmin Raj
Keyword(s):  
Deep Learning ◽  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action

Surgical Action Recognition with Spatiotemporal Convolutional Neural Networks

2019 ◽  
Author(s):  
Giacomo De Rossi ◽  
◽  
Nicola Piccinelli ◽  
Francesco Setti ◽  
Riccardo Muradore ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Action Recognition

Effective video feature for action recognition

2011 ◽  
Vol 31 (2) ◽  
pp. 406-409 ◽  
Author(s):  
Ying-jie LI ◽  
Yi-xin YIN ◽  
Fei DENG
Keyword(s):  
Action Recognition ◽  
Video Feature
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