Verbal and Object Counting

2020 ◽  
pp. 36-66
Author(s):  
Douglas H. Clements ◽  
Julie Sarama
Keyword(s):  
Object Counting

scholarly journals Moving Object Counting Using a Tripwire in H.265/HEVC Bitstreams for Video Surveillance

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 2529-2541 ◽  
Author(s):  
Yung-Wei Chen ◽  
Kai Chen ◽  
Shih-Yi Yuan ◽  
Sy-Yen Kuo
Keyword(s):  
Video Surveillance ◽  
Moving Object ◽  
Object Counting

scholarly journals An Advanced Deep Learning Approach for Multi-Object Counting in Urban Vehicular Environments

2021 ◽  
Vol 13 (12) ◽  
pp. 306
Author(s):  
Ahmed Dirir ◽  
Henry Ignatious ◽  
Hesham Elsayed ◽  
Manzoor Khan ◽  
Mohammed Adib ◽  
...  
Keyword(s):  
Deep Learning ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Weather Conditions ◽  
Research Area ◽  
Transportation Systems ◽  
Detection Accuracy ◽  
Adverse Weather ◽  
Object Counting ◽  
The Impact

Object counting is an active research area that gained more attention in the past few years. In smart cities, vehicle counting plays a crucial role in urban planning and management of the Intelligent Transportation Systems (ITS). Several approaches have been proposed in the literature to address this problem. However, the resulting detection accuracy is still not adequate. This paper proposes an efficient approach that uses deep learning concepts and correlation filters for multi-object counting and tracking. The performance of the proposed system is evaluated using a dataset consisting of 16 videos with different features to examine the impact of object density, image quality, angle of view, and speed of motion towards system accuracy. Performance evaluation exhibits promising results in normal traffic scenarios and adverse weather conditions. Moreover, the proposed approach outperforms the performance of two recent approaches from the literature.

Real-time Accurate Object Counting for Smart Farms

2019 ◽  
Author(s):  
Hao Shang ◽  
Rui Li ◽  
Xu He ◽  
Jilong Wang ◽  
Xinhui Peng
Keyword(s):  
Real Time ◽  
Object Counting

Deeply scale aggregation network for object counting

2020 ◽  
Vol 210 ◽  
pp. 106485
Author(s):  
He Li ◽  
Weihang Kong ◽  
Shihui Zhang
Keyword(s):  
Object Counting
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