Moving Object Detection based on Temporal and Spatial Resolution Mosaic

Moving Object Detection based on Temporal and Spatial Resolution Mosaic

Mohammed Abdel-Megeed SalemFaculty of Computer and Information Science,

Ain Shams University in [email protected]

Motivation

• Simultaneously accurate moving object detection and low computational complexity.

• Multiresolution analysis simplifies the process, improves its results, and allows real time processing.

• Representing the images in a mosaic of different resolutions

Moving Object Detection based on Temporal and Spatial Resolution Mosaic 01Mohammed A-Megeed Salem ICCES 2011

Outline

• Principles• Introduction• 3D Wavelet-based Algorithm• Mosaic-based Algorithm• Results and Analysis• Discussion and Conclusion

Moving Object Detection based on Temporal and Spatial Resolution Mosaic Mohammed A-Megeed Salem ICCES 2011

Principles• Resolution of analysis relevance of information

– High resolution => edges and objects of interest (local information)

– Low resolution => homogeneous regions and background (global information)

• Dimensionality of analysis dimensionality of information

– Images: 2D analysis => 2D spatial correlation between pixels– Videos: 3D analysis => 3D spatial and temporal features of the

motion


Outline



Introduction

Video Segmentation

Frame Differencing Optical Flow Background Subtraction


Outline



3D Wavelet-based Algorithm

Generating Binary Masks

Detection of Motion

Divide the sequence into group of frames

Input image sequence

Combine two subbands Xj = avrg(Dj4, Dj

7)

Apply the 3D wavelet transformd4

d7 x

After thresholding

After smoothing

After dilation

Thresholding

Median filtering

Dilation operation

Many levels analysis

Level of the extracted regions

Level of processing

Extraction of ROI and Active Traffic Area


3D Wavelet-based Algorithm

• The strong dependence between the resolution levels of the spatial and the temporal analyses

• All parts of the scene are analysed on the same resolution level

Detection of Motion

Input image sequence

D4

D7

XA D4 D2 D6 D1 D5 D3 D7

( )⋅φ ( )⋅ψ


Solution?• Independent spatial and temporal resolutions

– Low spatial resolution helps to avoid disturbances of the irrelevant motions that take place in background.

– Low temporal resolution means to miss the fast motion.

• Spatial resolution mosaic– Far views need to be processed in high spatial

resolution.– Close views need to be processed in low spatial

resolution.


Outline



The Mosaic Image

Resolution level

Information relevance

Temporal (3 rd) dimension


The Mosaic Map

High resolution for fine details

(small objects/far view)

.

.

.

Low resolution for global information

(big objects/close view)


The Algorithm

Image(Original

resolution)

Map

Different levels 2D wavelet transform

A H V D

Spatial transformation

Spatial resolution mosaic subbands


The Algorithm

Image(Original

resolution)

Map


A H V D

1D (temporal) wavelet transform


Temporal transformation

Temporal-spatial subbands

AA AD HA HD VA VD DA DD


Temporal 1D arrays


The Algorithm

Image(Original

resolution)

Map


A H V D

1D (temporal) wavelet transform


Temporal transformation

Temporal-spatial subbands

A D4 D2 D6 D1 D5 D3 D7

AA AD HA HD VA VD DA DD


Temporal 1D arrays


Outline



Results and Analysis



• False Alarms (FA):– The number of extracted regions that contain

no active moving objects.• Missed Objects (MO):

– The number of active moving objects that are not included in any extracted regions.

• Delayed Detections (DD):– The number of active moving objects that are

delayed for the first time detection.


Results and Analysis3D based Algorithm Mosaic based Algorithm


Outline



Discussion and Conclusion

• Automatic mosaic map

• High temporal resolution

• Time complexity is O(N2)


Discussion and Conclusion

• An algorithm based on resolution mosaic and 3D wavelet packet is proposed.

• The algorithm is based on analyzing the spatial domain independent of the temporal domain.

• A proper spatial resolution is chosen based on the relevance of the expected information.

• No need to have a compromise between the false alarm rates and the missed object rates.


ContactsMoving Object Detection based on Temporal and Spatial Resolution MosaicThe 2011 International Conference on Computer Engineering and Systems

November 29-30, December 1, 2011, Cairo, Egypt

Dr. Mohammed Abdel-Megeed M. Salem

Faculty of Computer and Information Sciences,Ain Shams University

Abbassia, Cairo, EgyptTel.: +2 011 1727 1050

Email: [email protected]

mailto:[email protected]

Moving Object Detection based on Temporal and Spatial Resolution Mosaic

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