An Efficient Video Inpainting Approach Using Deep Belief Network

作     者：M.Nuthal Srinivasan M.Chinnadurai 

作者机构：Department of Electronics and Communication EngineeringE.G.S.Pillay Engineering CollegeNagapattinam611002TamilnaduIndia Department of Computer Science and EngineeringE.G.S.Pillay Engineering CollegeNagapattinam611002TamilnaduIndia 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2022年第43卷第11期

页      面：515-529页

核心收录：

学科分类：0710[理学-生物学] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Video inpainting deep learning video restoration beetle antenna search deep belief network patch matching feature extraction 

摘      要：The video inpainting process helps in several video editing and restoration processes like unwanted object removal,scratch or damage rebuilding,and *** intends to fill spatio-temporal holes with reasonable content in the *** of the recent advancements of deep learning for image inpainting,it is challenging to outspread the techniques into the videos owing to the extra time *** this view,this paper presents an efficient video inpainting approach using beetle antenna search with deep belief network(VIA-BASDBN).The proposed VIA-BASDBN technique initially converts the videos into a set of frames and they are again split into a region of 5*5 *** addition,the VIABASDBN technique involves the design of optimal DBN model,which receives input features from Local Binary Patterns(LBP)to categorize the blocks into smooth or structured ***,the weight vectors of the DBN model are optimally chosen by the use of BAS ***,the inpainting of the smooth and structured regions takes place using the mean and patch matching approaches *** patch matching process depends upon the minimal Euclidean distance among the extracted SIFT features of the actual and references *** order to examine the effective outcome of the VIA-BASDBN technique,a series of simulations take place and the results denoted the promising performance.