Scene recognition in traffic surveillance system using Neural Network and probabilistic model

2017 ◽  
Author(s):  
Duong Nguyen-Ngoc Tran ◽  
Long Hoang Pham ◽  
Ha Manh Tran ◽  
Synh Viet-Uyen Ha
Keyword(s):  
Neural Network ◽  
Probabilistic Model ◽  
Surveillance System ◽  
Scene Recognition ◽  
Traffic Surveillance

scholarly journals Shadow Detection and Removal Technique using CNN

2021 ◽  
Vol 9 (8) ◽  
pp. 1748-1755
Author(s):  
Akanksha Bankhele
Keyword(s):  
Neural Network ◽  
Surveillance System ◽  
Shadow Detection ◽  
Loss Functions ◽  
Surveillance Systems ◽  
Traffic Surveillance ◽  
Real World Applications ◽  
Computer Vision Applications ◽  
Actual Target ◽  
Removal Technique

Abstract: The Shadow detection and removal Technique is used in many real-world applications, such as surveillance systems, computer vision applications and indoor outdoor system. The shape and orientation of an object, as well as the light source, can be revealed by shadows in an image. In a traffic surveillance system, the shadow can misclassify the actual target, lowering the system’s accuracy. Numerous algorithms and techniques have been developed by researchers to aid in the detection and removal of shadows in images. This paper aims to provide an overview of different shadow detection and removal techniques, their advantages and drawbacks. Also implementation of Convolutional Neural Network for shadow detection and OpenCV features to remove shadows by re-designing the output and analysing different loss functions to train the network. Keywords: Shadow Detection and Removal Techniques, Shadow Image Processing.

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