Human Detection and Tracking

2012 ◽  
Keyword(s):  
Human Detection ◽  
Detection And Tracking

scholarly journals Privacy-Aware Human-Detection and Tracking System Using Biological Signals

2019 ◽  
Vol E102.B (4) ◽  
pp. 708-721
Author(s):  
Toshihiro KITAJIMA ◽  
Edwardo Arata Y. MURAKAMI ◽  
Shunsuke YOSHIMOTO ◽  
Yoshihiro KURODA ◽  
Osamu OSHIRO
Keyword(s):  
Tracking System ◽  
Human Detection ◽  
Detection And Tracking ◽  
Biological Signals

scholarly journals Convolutional Neural Network Using Kalman Filter for Human Detection and Tracking on RGB-D Video

2018 ◽  
Vol 12 (2) ◽  
pp. 105 ◽  
Author(s):  
Jovin Angelico ◽  
Ken Ratri Retno Wardani
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Convolutional Neural Network ◽  
Human Detection ◽  
Detection Accuracy ◽  
Tracking Accuracy ◽  
Lighting Condition ◽  
Detection And Tracking ◽  
Computation Efficiency ◽  
The Impact

The computer ability to detect human being by computer vision is still being improved both in accuracy or computation time. In low-lighting condition, the detection accuracy is usually low. This research uses additional information, besides RGB channels, namely a depth map that shows objects’ distance relative to the camera. This research integrates Cascade Classifier (CC) to localize the potential object, the Convolutional Neural Network (CNN) technique to identify the human and nonhuman image, and the Kalman filter technique to track human movement. For training and testing purposes, there are two kinds of RGB-D datasets used with different points of view and lighting conditions. Both datasets have been selected to remove images which contain a lot of noises and occlusions so that during the training process it will be more directed. Using these integrated techniques, detection and tracking accuracy reach 77.7%. The impact of using Kalman filter increases computation efficiency by 41%.

Adaptive Filtering Methods for RSSI Signals in a Device-Free Human Detection and Tracking System

2019 ◽  
Vol 13 (3) ◽  
pp. 2998-3009 ◽  
Author(s):  
Apidet Booranawong ◽  
Nattha Jindapetch ◽  
Hiroshi Saito
Keyword(s):  
Adaptive Filtering ◽  
Tracking System ◽  
Human Detection ◽  
Detection And Tracking ◽  
Device Free

Partial Least Squares-Based Incremental PCA for Robust Human Detection and Tracking

2018 ◽  
Vol 24 (2) ◽  
pp. 1052-1056
Author(s):  
Benz Kek Yeo Chuen ◽  
Tee Connie ◽  
Ong Thian Song ◽  
Michael Kah Ong Goh
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Human Detection ◽  
Detection And Tracking ◽  
Incremental Pca

Fusing Monocular Vision and Laser Range Data for Human Detection and Tracking via Multi-Robot Collaboration

2012 ◽  
Vol 10 (8) ◽  
pp. 1607-1620 ◽  
Author(s):  
Yan Zhuang ◽  
Bo Li ◽  
Yisha Liu ◽  
Hongbo Liu
Keyword(s):  
Human Detection ◽  
Monocular Vision ◽  
Range Data ◽  
Laser Range ◽  
Detection And Tracking ◽  
Multi Robot
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