Fast and Robust Object Detection Framework in Compressed Domain

2005 ◽  
Author(s):  
A.M.A. Ahmad ◽  
B.M.A. Ahmad ◽  
Suh-Yin Lee
Keyword(s):  
Object Detection ◽  
Compressed Domain

scholarly journals Moving object detection in the H.264/AVC compressed domain

2016 ◽  
Vol 5 ◽  
Author(s):  
Marcus Laumer ◽  
Peter Amon ◽  
Andreas Hutter ◽  
André Kaup
Keyword(s):  
Object Detection ◽  
Moving Objects ◽  
Spatiotemporal Analysis ◽  
Temporal Analysis ◽  
Detection Algorithm ◽  
Single Step ◽  
Moving Object Detection ◽  
Moving Object ◽  
Compressed Domain ◽  
Video Streams

This paper presents a moving object detection algorithm for H.264/AVC video streams that is applied in the compressed domain. The method is able to extract and analyze several syntax elements from any H.264/AVC-compliant bit stream. The number of analyzed syntax elements depends on the mode in which the method operates. The algorithm is able to perform either a spatiotemporal analysis in a single step or a two-step analysis that starts with a spatial analysis of each frame, followed by a temporal analysis of several subsequent frames. Thereby, in each mode either only (sub-)macroblock types and partition modes or, additionally, quantization parameters are analyzed. The evaluation of these syntax elements enables the algorithm to determine a “weight” for each 4×4 block of pixels that indicates the level of motion within this block. A final segmentation after creating these weights segments each frame to foreground and background and hence indicates the positions and sizes of all moving objects. Our experiments show that the algorithm is able to efficiently detect moving objects in the compressed domain and that it is configurable to process a large number of parallel bit streams in real time.

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