scholarly journals AUTOMATIC FEATURE-BASED POINT CLOUD REGISTRATION FOR A MOVING SENSOR PLATFORM

Author(s):  
M. Weinmann ◽  
A. Dittrich ◽  
S. Hinz ◽  
B. Jutzi
2016 ◽  
Vol 136 (8) ◽  
pp. 1078-1084
Author(s):  
Shoichi Takei ◽  
Shuichi Akizuki ◽  
Manabu Hashimoto

2018 ◽  
Vol 30 (4) ◽  
pp. 642
Author(s):  
Guichao Lin ◽  
Yunchao Tang ◽  
Xiangjun Zou ◽  
Qing Zhang ◽  
Xiaojie Shi ◽  
...  

Author(s):  
Mahdi Saleh ◽  
Shervin Dehghani ◽  
Benjamin Busam ◽  
Nassir Navab ◽  
Federico Tombari

2020 ◽  
pp. 1-20
Author(s):  
Heng Yang ◽  
Jingnan Shi ◽  
Luca Carlone

2021 ◽  
Vol 137 ◽  
pp. 103042
Author(s):  
Qian Xie ◽  
Yiming Zhang ◽  
Xuanming Cao ◽  
Yabin Xu ◽  
Dening Lu ◽  
...  

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3848
Author(s):  
Xinyue Zhang ◽  
Gang Liu ◽  
Ling Jing ◽  
Siyao Chen

The heart girth parameter is an important indicator reflecting the growth and development of pigs that provides critical guidance for the optimization of healthy pig breeding. To overcome the heavy workloads and poor adaptability of traditional measurement methods currently used in pig breeding, this paper proposes an automated pig heart girth measurement method using two Kinect depth sensors. First, a two-view pig depth image acquisition platform is established for data collection; the two-view point clouds after preprocessing are registered and fused by feature-based improved 4-Point Congruent Set (4PCS) method. Second, the fused point cloud is pose-normalized, and the axillary contour is used to automatically extract the heart girth measurement point. Finally, this point is taken as the starting point to intercept the circumferential perpendicular to the ground from the pig point cloud, and the complete heart girth point cloud is obtained by mirror symmetry. The heart girth is measured along this point cloud using the shortest path method. Using the proposed method, experiments were conducted on two-view data from 26 live pigs. The results showed that the heart girth measurement absolute errors were all less than 4.19 cm, and the average relative error was 2.14%, which indicating a high accuracy and efficiency of this method.


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