NDLI: Hierarchical video object segmentation

Content Provider	IEEE Xplore Digital Library
Author	Junliang Xing Haizhou Ai Shihong Lao
Copyright Year	2011
Description	Author affiliation: Dept. of Computer Science and Technology, Tsinghua Univ., Beijing 100084, China (Junliang Xing; Haizhou Ai) \|\| Development Center, OMRON Social Solutions Co., LTD., Kyoto 619-0283, Japan (Shihong Lao)
Abstract	In this paper, we propose a general video object segmentation framework which views object segmentation from a unified Bayesian perspective and optimizes the MAP formulated problem in a progressive manner. Based on object detection and tracking results, a three-level hierarchical video object segmentation approach is presented. At the first level, an offline learned segmentor is applied to each object tracking result of current frame to get a coarse segmentation. At the second level, the coarse segmentation is updated into an intermediate segmentation by a temporal model which propagates the fine segmentation of previous frame to current frame based on a discriminative feature points voting process. At the third level, the intermediate segmentation is refined by an iterative procedure which uses online collected color-and-shape information to get the final result. We apply the approach to pedestrian segmentation on many challenging datasets that demonstrates its effectiveness.
Starting Page	67
Ending Page	71
File Size	2069320
Page Count	5
File Format	PDF
ISBN	9781457701221
e-ISBN	9781457701214
DOI	10.1109/ACPR.2011.6166705
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Accuracy Shape Image color analysis Tracking Segmentation Video sequences Object segmentation Detectors Object detection
Content Type	Text
Resource Type	Article

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