TY - JOUR
KW - Patterns
KW - Human-Computer Interaction (HCI)
KW - Recognition
KW - Feature Extraction
KW - Video Surveillance
AU - Vijay Bhaskar-Semwal
AU - Pushkar Dixit
AU - Nishant Singh
AU - Jay Prakash Gupta
AB - Human activity recognition based on the computer vision is the process of labelling image sequences with action labels. Accurate systems for this problem are applied in areas such as visual surveillance, human computer interaction and video retrieval. The challenges are due to variations in motion, recording settings and gait differences. Here we propose an approach to recognize the human activities through gait. Activity recognition through Gait is the process of identifying an activity by the manner in which they walk. The identification of human activities in a video, such as a person is walking, running, jumping, jogging etc are important activities in video surveillance. We contribute the use of Model based approach for activity recognition with the help of movement of legs only. Experimental results suggest that our method are able to recognize the human activities with a good accuracy rate and robust to shadows present in the videos.
IS - Special Issue on Multisensor User Tracking and Analytics to Improve Education and other Application Fields
M1 - 7
N2 - Human activity recognition based on the computer vision is the process of labelling image sequences with action labels. Accurate systems for this problem are applied in areas such as visual surveillance, human computer interaction and video retrieval. The challenges are due to variations in motion, recording settings and gait differences. Here we propose an approach to recognize the human activities through gait. Activity recognition through Gait is the process of identifying an activity by the manner in which they walk. The identification of human activities in a video, such as a person is walking, running, jumping, jogging etc are important activities in video surveillance. We contribute the use of Model based approach for activity recognition with the help of movement of legs only. Experimental results suggest that our method are able to recognize the human activities with a good accuracy rate and robust to shadows present in the videos.
PY - 2014
SP - 7
EP - 16
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - Analysis of Gait Pattern to Recognize the Human Activities
UR - http://www.ijimai.org/JOURNAL/sites/default/files/files/2014/09/ijimai20142_7_1_pdf_23675.pdf
VL - 2
SN - 1989-1660
ER -