Background subtraction driven seeds selection for moving objects segmentation and matting

نویسندگان

  • Bineng Zhong
  • Yan Chen
  • Yewang Chen
  • Rongrong Ji
  • Ying Chen
  • Duansheng Chen
  • Hanzi Wang
چکیده

In this paper, we address the difficult task of moving objects segmentation and matting in dynamic scenes. Toward this end, we propose a new automatic way to integrate a background subtraction (BGS) and an alpha matting technique via a heuristic seeds selection scheme. Specifically, our method can be divided into three main steps. First, we use a novel BGS method as attention mechanisms, generating possible. Second, a connected components algorithm is used to give the bounding boxes of the labeled foreground pixels. Finally, matting of the object associated to a given bounding box is performed using a heuristic seeds selection scheme. This matting task is guided by top-down knowledge. Experimental results demonstrate the efficiency and effectiveness of our method. & 2012 Elsevier B.V. All rights reserved.

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

Surveillance Video Synopsis Based on Moving Object Matting Using Non- interactive GrabCut

An algorithm of surveillance video synopsis is presented in this paper. At first, the detection method of moving object for surveillance video is proposed. Then the ROI (Region of Interest) of moving object is extracted and a noninteractive matting algorithm of moving object based on GrabCut is presented. These matting moving objects are placed without overlapping in a background image, so a fr...

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

A Generic Feature Selection Method for Background Subtraction Using Global Foreground Models

Over the last few years, a wide variety of background subtraction algorithms have been proposed for the detection of moving objects in videos acquired with a static camera. While much effort have been devoted to the development of robust background models, the automatic spatial selection of useful features for representing the background has been neglected. In this paper, we propose a generic a...

متن کامل

A PRACTICAL APPROACH TO REAL-TIME DYNAMIC BACKGROUND GENERATION BASED ON A TEMPORAL MEDIAN FILTER

In many computer vision applications, segmenting and extraction of moving objects in video sequences is an essential task. Background subtraction, by which each input image is subtracted from the reference image, has often been used for this purpose. In this paper, we offer a novel background-subtraction technique for real-time dynamic background generation using color images that are taken fro...

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:
  • Neurocomputing

دوره 103  شماره 

صفحات  -

تاریخ انتشار 2013