Sensing Motion by Monitoring and Detection of Moving Objects

نویسندگان

  • Arshdeep Singh
  • Richard J. Radke
  • Srinivas Andra
  • Qiang Liu
  • Robert J. Sclabassi
  • Lijing Zhang
  • Xiaofei Ji
  • Honghai Liu
  • Hazi Wang
  • K. S. Tan
  • R. Saatchi
  • Yuki Fujimori
  • Yoshiyuki Ohmura
  • Mohamed F. Abdelkader
  • Ching Yee Yong
  • Rubita Sudirman
  • Kim Mey Chew
  • Suwich Tirakoat
  • Francesco Cardile
  • Giancarlo Iannizzotto
  • Nan Lu
  • Jihong Wang
  • Q. H. Wu
چکیده

Detection of movement of objects is very important in various areas. In this paper we present various techniques related to motion detection of moving objects. Existing methods for moving object detection are mainly the frame subtraction method, the background subtraction method and the optical flow method. The aim is to develop mathematical models, algorithms and technologies to build a machine with vision capabilities as advanced at least as human eyesight.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Motion detection by a moving observer using Kalman filter and neural network in soccer robot

In many autonomous mobile applications, robots must be capable of analyzing motion of moving objects in their environment. Duringmovement of robot the quality of images is affected by quakes of camera which cause high errors in image processing outputs. In thispaper, we propose a novel method to effectively overcome this problem using Neural Networks and Kalman Filtering theory. Thistechnique u...

متن کامل

Statistical Background Modeling Based on Velocity and Orientation of Moving Objects

Background modeling is an important step in moving object detection and tracking. In this paper, we propose a new statistical approach in which, a sequence of frames are selected according to velocity and direction of some moving objects and then an initial background is modeled, based on the detection of gray pixel's value changes. To have used this sequence of frames, no estimator or distribu...

متن کامل

Moving Objects Tracking Using Statistical Models

Object detection plays an important role in successfulness of a wide range of applications that involve images as input data. In this paper we have presented a new approach for background modeling by nonconsecutive frames differencing. Direction and velocity of moving objects have been extracted in order to get an appropriate sequence of frames to perform frame subtraction. Stationary parts of ...

متن کامل

Moving Objects Tracking Using Statistical Models

Object detection plays an important role in successfulness of a wide range of applications that involve images as input data. In this paper we have presented a new approach for background modeling by nonconsecutive frames differencing. Direction and velocity of moving objects have been extracted in order to get an appropriate sequence of frames to perform frame subtraction. Stationary parts of ...

متن کامل

Tracking Multiple Moving Objects Using Unscented Kalman Filtering Techniques

It is an important task to reliably detect and track multiple moving objects for video surveillance and monitoring. However, when occlusion occurs in nonlinear motion scenarios, many existing methods often fail to continuously track multiple moving objects of interest. In this paper we propose an effective approach for detection and tracking of multiple moving objects with occlusion. Moving tar...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015