scholarly journals Obstacle detection and tracking algorithm based on multi‐lidar fusion in urban environment

2021 ◽  
Author(s):  
Jiong Li ◽  
Yu Zhang ◽  
Xixia Liu ◽  
Xudong Zhang ◽  
Rui Bai
Keyword(s):  
Urban Environment ◽  
Obstacle Detection ◽  
Tracking Algorithm ◽  
Detection And Tracking

Applications for a people detection and tracking algorithm using a time-of-flight camera

2014 ◽  
Vol 75 (17) ◽  
pp. 10769-10786 ◽  
Author(s):  
Carsten Stahlschmidt ◽  
Alexandros Gavriilidis ◽  
Jörg Velten ◽  
Anton Kummert
Keyword(s):  
Time Of Flight ◽  
Tracking Algorithm ◽  
People Detection ◽  
Detection And Tracking

Unmanned vehicle dynamic obstacle detection, tracking and recognition method based on laser sensor

2021 ◽  
Vol 14 (2) ◽  
pp. 239-251
Author(s):  
Hualei Zhang ◽  
Mohammad Asif Ikbal
Keyword(s):  
Feature Fusion ◽  
Obstacle Detection ◽  
Geometric Features ◽  
Recognition Method ◽  
Content Type ◽  
Detection And Tracking ◽  
Spatio Temporal ◽  
Dynamic Obstacle ◽  
Real Vehicle ◽  
Temporal Feature

PurposeIn response to these shortcomings, this paper proposes a dynamic obstacle detection and tracking method based on multi-feature fusion and a dynamic obstacle recognition method based on spatio-temporal feature vectors.Design/methodology/approachThe existing dynamic obstacle detection and tracking methods based on geometric features have a high false detection rate. The recognition methods based on the geometric features and motion status of dynamic obstacles are greatly affected by distance and scanning angle, and cannot meet the requirements of real traffic scene applications.FindingsFirst, based on the geometric features of dynamic obstacles, the obstacles are considered The echo pulse width feature is used to improve the accuracy of obstacle detection and tracking; second, the space-time feature vector is constructed based on the time dimension and space dimension information of the obstacle, and then the support vector machine method is used to realize the recognition of dynamic obstacles to improve the obstacle The accuracy of object recognition. Finally, the accuracy and effectiveness of the proposed method are verified by real vehicle tests.Originality/valueThe paper proposes a dynamic obstacle detection and tracking method based on multi-feature fusion and a dynamic obstacle recognition method based on spatio-temporal feature vectors. The accuracy and effectiveness of the proposed method are verified by real vehicle tests.

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