PixelSieve: Towards Efficient Activity Analysis From Compressed Video Streams

2021 ◽  
Author(s):  
Yongchen Wang ◽  
Ying Wang ◽  
Huawei Li ◽  
Xiaowei Li
Keyword(s):  
Activity Analysis ◽  
Compressed Video ◽  
Video Streams

scholarly journals Characterizing perceptual artifacts in compressed video streams

2014 ◽  
Author(s):  
Kai Zeng ◽  
Tiesong Zhao ◽  
Abdul Rehman ◽  
Zhou Wang
Keyword(s):  
Compressed Video ◽  
Video Streams

scholarly journals Implementation of Dynamic Threshold Method for Human Motion Detection in Video surveillance application

2014 ◽  
Vol 13 (8) ◽  
pp. 4776-4781
Author(s):  
Ms. Pritee Gupta ◽  
Dr. Yashpal Singh
Keyword(s):  
Moving Objects ◽  
Activity Analysis ◽  
Human Motion ◽  
Moving Object ◽  
Video Streams ◽  
Threshold Method ◽  
Human Motion Detection ◽  
Object Based ◽  
Computer Vision Applications ◽  
Surveillance Application

 Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later steps more efficient. This paper implemented a method to detect moving object based on background subtraction. First of all, we establish a reliable background updating model based on statistical and use a dynamic optimization threshold method to obtain a more complete moving object. The moving human bodies are accurately and reliably detected. The experiment results show that the proposed method runs quickly, accurately and fits for the real-time detection.

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