Moving object detection

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MOVING OBJECT DETECTION

Presentation By:Deepak Gambhir Saurabh Sharma Manav Mittal(ICE-III,BVCOE) (ECE-IV,BVCOE) (ICE-III,BVCOE)

CONTEXT OF PAPER

Algorithm for object detectionBy calculating RGB content &

Illumination.

PLATFORMS

• MATLAB(Digital image processing)

• Experimental Result Reports

Objective

• To find the RGB content of the moving object.• To find the illumintaion.

Basic principle

According to physics, an object is considered to be colorless until the light of suitable wavelength falls on it.

The color of the object is decided by the amount of wavelength absorbed and reflected by the object, which states that the “amount of light falling on an object determines the color of the image”.

illumintaion- property of light which varies according to the object.

It changes its value even if the object is

observed from stationary position at time (t1) to motion position at time( t2).

This change in illumination causes its color to change a bit thus changing the RGB configuration which is used to get the desired result.

EXPERIMENTAL DATA

1) Stationary object and stationary environment

Amount of illumination

2) Stationary environment and partially moving object

Amount of illumination

3) Stationary environment and object moving alongwith body

Amount of illumination

Evaluation

The detection of object can be done on the comparison of illumination and RGB configuration.

• As the object attains a velocity, the RGB configuration of the object changes due to change in illumination.

• The detection of object can be done on the basis of illumination and RGB configuration.

Conclusions

Limitations

• Difficult to detect objects in dark.• Slow moving objects couldn’t be detected

too.

Future Aspects• SECURITY SYSTEM: The object to be

detected always faces by a camera and as the object attains a velocity, the RGB configuration of the object changes due to change in illumination. Hardware should be design in such a way that as the camera changes its position an alarm gets activated.

• The detection of lip movements so as to design a device that can change the movement of lips into speech recognition so that person with the disabilities to recognize the frequency is able to communicate without any problem.

REFERENCES• Reid Porter, Neil Harvey, James Theiler,”a change detection

approach to moving object detection in low frame –rate video”, space and remote sensing sciences group.

• Jong Bae Kim, Schof Comput Eng., Seoul Digital University, Seoul• Tao Xia1, Chaoqiang Liu2, Hui Li2,”efficient moving object detection

and description, National Singapore University• 4)Michal Irani, P. Anandan, David Sarnoff Research Center, “a

unified approach to a moving object detection in 2D and 3D scenes”.

• Mrs. Renuka S. Sindge Department Of IT Govt. Polytechnic College, Mrs. Shubhangisapkal Department of Comp. Sciences Govt. College of engineering “multiple object detection from real time video sequence”

• J.H Park1, G.S.Lee1, W.H.Cho2, Chhonam National University, N.Taon1, S.H..Kim1, S.Y.Park3, Mokpo National University, “moving object based detection based on clauses entropy”.

• Fu-Yuan Hu, Yan-Ning Zhan, Lan Yao, “an effective detection algorithm for moving object with complex background”, Northwestern Poly-Technical University.

• Zhan Chaohui Duan Xiaohui, Xu Shuoyu Song Zheng Luo Min, “an improved moving object detection algorithm based on frame difference and edge detection”, Peking University.

• Victor Mejia*, Eun-Young Kang “automatic moving object detection using motion and color features and bi-model Gaussian approximation”. California State University

• Jiman Kimam, Guensu Ye, Daijan Kim “moving object detection under free-moving camera”, Pohang University of Science and Technology

• Chen Peijiang, “moving object detection based on the background extraction”, Linyi Normal University

• Chin Chun Huang and Sheng-Jyh Wang, “a cascaded hierarchical framework for moving bject detection”, National Chio Tung University, Taiwan

• Ben-Hsiang do, Shih-Chia Huang, “dyamic background modeling based on radial basis function neural networks for moving object detection”, National Taipei University of Technology.

• Jacinto Nascimento, Jorge Marques, “performance evaluation of object detection algorithms for video survEillence”, Member, IEEE.

THANK YOU

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