Open AccessObject Recognition Based on Improved Context Model
Author(s) -
Wen Chenglin,
Zhou Guangfu,
Gao Jingli,
Li Hongwei,
Xu Xiaobin
Publication year - 2018
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2018.03.014
Subject(s) - computer science , context (archaeology) , object (grammar) , artificial intelligence , geology , paleontology
An object recognition method is proposed in this paper by introducing the spatial location relationship of objects into the context model. The spatial‐position information of the objects is first utilized to model the context model. The model parameters and dependency structure of objects can be learned by integrating the context information into the same probabilistic framework. The image recognition is accomplished by using the advantages of efficient inference of the tree structure model. The proposed method can greatly improve the object recognition rate and better keep the consistency of scenes. The effectiveness of the proposed algorithm is verified by testing and comparing with other existing algorithms in the actual dataset.