Height estimation of a pedestrian based on an image

2015 ◽  
Author(s):  
S. M. Kim ◽  
J. K. Song ◽  
B. W. Yoon ◽  
J. S. Park
Keyword(s):  
Height Estimation

The applicability of the Carrea’s method for human height estimation through lower and upper teeth in dental models

2018 ◽  
Vol 3 (1) ◽  
pp. 16-22
Author(s):  
Julius Cézar Alves de LIMA ◽  
Yane Laiza da Silva OLIVEIRA ◽  
Patricia Moreira RABELLO ◽  
Yuri Wanderley CAVALCANTI ◽  
Bianca Marques SANTIAGO
Keyword(s):  
Height Estimation ◽  
Human Height ◽  
Dental Models

scholarly journals Multi-Scene Building Height Estimation Method Based on Shadow in High Resolution Imagery

2021 ◽  
Vol 13 (15) ◽  
pp. 2862
Author(s):  
Yakun Xie ◽  
Dejun Feng ◽  
Sifan Xiong ◽  
Jun Zhu ◽  
Yangge Liu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Estimation Method ◽  
Absolute Error ◽  
Large Error ◽  
Estimation Methods ◽  
Height Estimation ◽  
Building Height ◽  
Remote Sensing Imagery ◽  
High Resolution Imagery

Accurately building height estimation from remote sensing imagery is an important and challenging task. However, the existing shadow-based building height estimation methods have large errors due to the complex environment in remote sensing imagery. In this paper, we propose a multi-scene building height estimation method based on shadow in high resolution imagery. First, the shadow of building is classified and described by analyzing the features of building shadow in remote sensing imagery. Second, a variety of shadow-based building height estimation models is established in different scenes. In addition, a method of shadow regularization extraction is proposed, which can solve the problem of mutual adhesion shadows in dense building areas effectively. Finally, we propose a method for shadow length calculation combines with the fish net and the pauta criterion, which means that the large error caused by the complex shape of building shadow can be avoided. Multi-scene areas are selected for experimental analysis to prove the validity of our method. The experiment results show that the accuracy rate is as high as 96% within 2 m of absolute error of our method. In addition, we compared our proposed approach with the existing methods, and the results show that the absolute error of our method are reduced by 1.24 m-3.76 m, which can achieve high-precision estimation of building height.

scholarly journals Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning

2021 ◽  
Vol 172 ◽  
pp. 79-94
Author(s):  
Maryam Pourshamsi ◽  
Junshi Xia ◽  
Naoto Yokoya ◽  
Mariano Garcia ◽  
Marco Lavalle ◽  
...  
Keyword(s):  
Machine Learning ◽  
Tropical Forest ◽  
Forest Canopy ◽  
Canopy Height ◽  
Polarimetric Sar ◽  
Height Estimation ◽  
Tropical Forest Canopy

scholarly journals Canopy Height Estimation in Mediterranean Forests of Spain with TanDEM-X Data

2021 ◽  
pp. 1-1
Author(s):  
Cristina Gomez ◽  
Juan M Lopez-Sanchez ◽  
Noelia Romero-Puig ◽  
Jianjun Zhu ◽  
Haiqiang Fu ◽  
...  
Keyword(s):  
Canopy Height ◽  
Mediterranean Forests ◽  
Height Estimation

Forest Height Estimation from Tandem-X InSAR Coherence Magnitude Towards Large Scale Applications

2020 ◽  
Author(s):  
Changhyun Choi ◽  
Roman Guliaev ◽  
Victor Cazcarra-Bes ◽  
Matteo Pardini ◽  
Konstantinos P. Papathanassiou
Keyword(s):  
Large Scale ◽  
Height Estimation ◽  
Forest Height

Accuracy of Building Height Estimation from SAR Images

2006 ◽  
Author(s):  
G. Franceschetti ◽  
R. Guida ◽  
A. Iodice ◽  
D. Riccio ◽  
G. Ruello
Keyword(s):  
Sar Images ◽  
Height Estimation ◽  
Building Height

Impacts of topography for forest height estimation

2012 ◽  
Author(s):  
Wenmei Li ◽  
Erxue Chen ◽  
Zengyuan Li ◽  
Hanwei Sun ◽  
Tao Zeng ◽  
...  
Keyword(s):  
Height Estimation ◽  
Forest Height
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