A Dynamic Feature Fusion Strategy for Magnetic Field and Wi-Fi Based Indoor Positioning

2019 ◽  
Author(s):  
Yichen Du ◽  
Tughrul Arslan ◽  
Qianqian Shen
Keyword(s):  
Magnetic Field ◽  
Feature Fusion ◽  
Indoor Positioning ◽  
Dynamic Feature ◽  
Fusion Strategy

scholarly journals Dynamic Feature Fusion for Semantic Edge Detection

2019 ◽  
Author(s):  
Yuan Hu ◽  
Yunpeng Chen ◽  
Xiang Li ◽  
Jiashi Feng
Keyword(s):  
Edge Detection ◽  
Multiple Scales ◽  
Feature Fusion ◽  
Detection Methods ◽  
Local Context ◽  
Dynamic Feature ◽  
Feature Maps ◽  
Fusion Strategy ◽  
Fixed Weight ◽  
Fusion Methods

Features from multiple scales can greatly benefit the semantic edge detection task if they are well fused. However, the prevalent semantic edge detection methods apply a fixed weight fusion strategy where images with different semantics are forced to share the same weights, resulting in universal fusion weights for all images and locations regardless of their different semantics or local context. In this work, we propose a novel dynamic feature fusion strategy that assigns different fusion weights for different input images and locations adaptively. This is achieved by a proposed weight learner to infer proper fusion weights over multi-level features for each location of the feature map, conditioned on the specific input. In this way, the heterogeneity in contributions made by different locations of feature maps and input images can be better considered and thus help produce more accurate and sharper edge predictions. We show that our model with the novel dynamic feature fusion is superior to fixed weight fusion and also the na\"ive location-invariant weight fusion methods, via comprehensive experiments on benchmarks Cityscapes and SBD. In particular, our method outperforms all existing well established methods and achieves new state-of-the-art.

scholarly journals A Comprehensive Analysis of Magnetic Field Based Indoor Positioning With Smartphones: Opportunities, Challenges and Practical Limitations

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 228548-228571
Author(s):  
Imran Ashraf ◽  
Yousaf Bin Zikria ◽  
Soojung Hur ◽  
Yongwan Park
Keyword(s):  
Magnetic Field ◽  
Indoor Positioning ◽  
Comprehensive Analysis

Anti-Occlusion Algorithm for Object Tracking Based on Multi-Feature Fusion

2014 ◽  
Vol 610 ◽  
pp. 393-400
Author(s):  
Jie Cao ◽  
Xuan Liang
Keyword(s):  
Object Tracking ◽  
Feature Fusion ◽  
Experimental Results ◽  
Occlusion Detection ◽  
Fusion Algorithm ◽  
Fusion Strategy ◽  
Complex Background ◽  
Complex Scenes

Complex background, especially when the object is similar to the background in color or the target gets blocked, can easily lead to tracking failure. Therefore, a fusion algorithm based on features confidence and similarity was proposed, it can adaptively adjust fusion strategy when occlusion occurs. And this confidence is used among occlusion detection, to overcome the problem of inaccurate occlusion determination when blocked by analogue. The experimental results show that the proposed algorithm is more robust in the case of the cover, but also has good performance under other complex scenes.

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