Noise Reduction of Video Sequences Using Fuzzy Logic Motion Detection

2005 ◽  
pp. 666-673
Author(s):  
Stefan Schulte ◽  
Vladimir Zlokolica ◽  
Aleksandra Pizurica ◽  
Wilfried Philips ◽  
Etienne Kerre
Keyword(s):  
Fuzzy Logic ◽  
Noise Reduction ◽  
Motion Detection ◽  
Video Sequences

Motion detection using fuzzy logic comparator

1995 ◽  
Vol 41 (2) ◽  
pp. 360-366
Author(s):  
V. Gustin ◽  
M. Cufer
Keyword(s):  
Fuzzy Logic ◽  
Motion Detection

MOVING CAMERA MOVING OBJECT SEGMENTATION IN COMPRESSED VIDEO SEQUENCES

2009 ◽  
Vol 09 (04) ◽  
pp. 609-627 ◽  
Author(s):  
J. WANG ◽  
N. V. PATEL ◽  
W. I. GROSKY ◽  
F. FOTOUHI
Keyword(s):  
Motion Detection ◽  
Object Segmentation ◽  
Object Motion ◽  
Moving Object ◽  
Transformation Model ◽  
Video Sequences ◽  
Compressed Domain ◽  
Camera Motion ◽  
Consistency Check ◽  
Moving Object Segmentation

In this paper, we address the problem of camera and object motion detection in the compressed domain. The estimation of camera motion and the moving object segmentation have been widely stated in a variety of context for video analysis, due to their capabilities of providing essential clues for interpreting the high-level semantics of video sequences. A novel compressed domain motion estimation and segmentation scheme is presented and applied in this paper. MPEG-2 compressed domain information, namely Motion Vectors (MV) and Discrete Cosine Transform (DCT) coefficients, is filtered and manipulated to obtain a dense and reliable Motion Vector Field (MVF) over consecutive frames. An iterative segmentation scheme based upon the generalized affine transformation model is exploited to effect the global camera motion detection. The foreground spatiotemporal objects are separated from the background using the temporal consistency check to the output of the iterative segmentation. This consistency check process can coalesce the resulting foreground blocks and weed out unqualified blocks. Illustrative examples are provided to demonstrate the efficacy of the proposed approach.

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