Bag-of-words based loop-closure detection in visual SLAM

2018 ◽  
Author(s):  
Jiachen Zhang ◽  
Dahang Ai ◽  
Yi Xiang ◽  
Yi Wang ◽  
Xiaodong Chen ◽  
...  
Keyword(s):  
Bag Of Words ◽  
Visual Slam ◽  
Loop Closure ◽  
Loop Closure Detection

scholarly journals A BigBiGAN-Based Loop Closure Detection Algorithm for Indoor Visual SLAM

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Qiubo Zhong ◽  
Xiaoyi Fang
Keyword(s):  
Unsupervised Learning ◽  
Recall Rate ◽  
Detection Algorithm ◽  
Detection Methods ◽  
Bag Of Words ◽  
Learning Method ◽  
Visual Slam ◽  
Loop Closure ◽  
Loop Closure Detection ◽  
Main Component

Loop closure detection serves as the fulcrum of improving the accuracy and precision in simultaneous localization and mapping (SLAM). The majority of loop detection methods extract artificial features, which fall short of learning comprehensive data information, but unsupervised learning as a typical deep learning method excels in self-access learning and clustering to analyze the similarity without handling the data. Moreover, the unsupervised learning method does solve restrictions on image quality and singleness semantics in many traditional SLAM methods. Therefore, a loop closure detection strategy based on an unsupervised learning method is proposed in this paper. The main component adopts BigBiGAN to extract features and establish an original bag of words. Then, the complete bag of words is used to detect loop closing. Finally, a considerable validation check of the ORB descriptor is added to verify the result and output outcome of loop closure detection. The proposed algorithm and other compared algorithms are, respectively, applied on Autolabor Pro1 to execute the indoor visual SLAM. The experiment shows that the proposed algorithm increases the recall rate by 20% compared with ORB-SLAM2 and LSD-SLAM. And it also improves at least 40.0% accuracy than others and reduces 14% time loss of ORB-SLAM2. Therefore, the presented SLAM based on BigBiGAN does benefit much the visual SLAM in the indoor environment.

Edge-Based Loop Closure Detection in Visual SLAM

2018 ◽  
Author(s):  
Dario F. Mendieta ◽  
Francisco Raverta Capua ◽  
Juan Jose Tarrio ◽  
Marcelo L. Moreyra
Keyword(s):  
Visual Slam ◽  
Loop Closure ◽  
Loop Closure Detection ◽  
Edge Based

Sequence-based sparse optimization methods for long-term loop closure detection in visual SLAM

2018 ◽  
Vol 42 (7) ◽  
pp. 1323-1335 ◽  
Author(s):  
Fei Han ◽  
Hua Wang ◽  
Guoquan Huang ◽  
Hao Zhang
Keyword(s):  
Optimization Methods ◽  
Sparse Optimization ◽  
Visual Slam ◽  
Loop Closure ◽  
Loop Closure Detection

Loop Closure Detection of Visual SLAM Based on Improved LBD and Data-Dependent Measure

2021 ◽  
Vol 58 (6) ◽  
pp. 0615001
Author(s):  
史佳豪 Shi Jiahao ◽  
孟庆浩 Meng Qinghao ◽  
戴旭阳 Dai Xuyang
Keyword(s):  
Dependent Measure ◽  
Visual Slam ◽  
Loop Closure ◽  
Loop Closure Detection
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