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1. 发明申请

WO2008152607A1 METHOD, APPARATUS, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR DEPTH-RELATED INFORMATION PROPAGATION 审中-公开
标题翻译：方法，装置，系统和计算机程序产品深度相关信息传播
公开(公告)号：WO2008152607A1
公开(公告)日：2008-12-18
申请号：PCT/IB2008/052340
申请日：2008-06-13
申请人： KONINKLIJKE PHILIPS ELECTRONICS N.V. , PHILIPS INTELLECTUAL PROPERTY & STANDARDS GMBH , PHILOMIN, Vasanth , LIU, Fang , SHEN, Chunfeng
发明人： PHILOMIN, Vasanth , LIU, Fang , SHEN, Chunfeng
IPC分类号： H04N13/00
CPC分类号： G06T7/579 , G06T7/215 , G06T7/277 , G06T2207/10016 , G06T2207/20076 , G06T2207/30241 , H04N13/128 , H04N13/261
摘要： The present invention relates to an apparatus, a system, a method and a computer program product of propagating depth-related information and segmentation.related information associated with at least one image from an image sequence to a consecutive image in the image sequence using a probabilistic network. The method comprising use of the probabilistic network to solve a Bayesian labeling problem wherein the labeling comprises the depth-related information and segmentation.related information and wherein the node links of the probabilistic network are configured to simultaneously account for constraints imposed by the depth-related information and segmentation.related information of the consecutive image and mapping information for the respective node from the at least one image to the consecutive image. The nodes taking into account evidence in the form of image characteristics from the consecutive image, such that propagated depth- related information and segmentation.related information is established for the consecutive image by establishing a Maximum A Posteriori solution for both the labeling and the mapping. The Bayesian problem comprises segmentation of the consecutive image, and propagation of depth information, based on segmentation and mapping information stored in the probabilistic network constructed from the at least one image to the consecutive image.
摘要翻译：本发明涉及一种将图像序列中的至少一个图像与图像序列中的连续图像相关联的与深度相关信息和分割相关信息的装置，系统，方法和计算机程序产品，其使用概率网络。该方法包括使用概率网络来解决贝叶斯标注问题，其中标签包括深度相关信息和分段相关信息，并且其中概率网络的节点链路被配置为同时考虑与深度相关的约束连续图像的信息和分割相关信息以及从至少一个图像到连续图像的各个节点的映射信息。考虑到来自连续图像的图像特征形式的证据的节点，通过为标签和映射建立最大A后验解，为连续图像建立传播的深度相关信息和分段相关信息。贝叶斯问题包括基于从至少一个图像构建的概率网络中存储的分割和映射信息到连续图像的连续图像的分割和深度信息的传播。

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