Semi-Supervised Video Segmentation Using Tree Structured Graphical Models

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Semi-supervised structured prediction models

Learning mappings between arbitrary structured input and output variables is a fundamental problem in machine learning. It covers many natural learning tasks and challenges the standard model of learning a mapping from independently drawn instances to a small set of labels. Potential applications include classification with a class taxonomy, named entity recognition, and natural language parsin...

متن کامل

Semi-supervised Video Object Segmentation Using Multiple Random Walkers

A semi-supervised video object segmentation algorithm using multiple random walkers (MRW) is proposed in this work. We develop an initial probability estimation scheme that minimizes an objective function to roughly separate the foreground from the background. Then, we simulate MRW by employing the foreground and background agents. During the MRW process, we update restart distributions using a...

متن کامل

Video Image Segmentation with Graphical Models

Video image segmentation plays an important role in video processing and computer vision. This talk gives a brief introduction to some popular segmentation approaches based on the graphical models. A successful deterministic method maps the image segmentation into a minimum graph cut problem. Stochastic approaches are mainly based on the Gibbs sampler. We adopt the Potts model with external fie...

متن کامل

Video Segmentation Based on Graphical Models

This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notions of distance transformation and Markov random field are used to express spatio-temporal constraints. Given consecutive frames, an optimiz...

متن کامل

Image Segmentation Using Semi-Supervised k-Means

Extracting the region of interest is a very challenging task in Image Processing. Image segmentation is an important technique for image processing which aims at partitioning the image into different homogeneous regions or clusters. Lots of general-purpose techniques and algorithms have been developed and widely applied in various application areas. In this paper, a Semi-Supervised k-means segm...

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

ژورنال

عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence

سال: 2013

ISSN: 0162-8828,2160-9292

DOI: 10.1109/tpami.2013.54