Journal of Signal and Information Processing

Journal of Signal and Information Processing

ISSN Print: 2159-4465
ISSN Online: 2159-4481
www.scirp.org/journal/jsip
E-mail: jsip@scirp.org
"Video Frame’s Background Modeling: Reviewing the Techniques"
written by Hamid Hassanpour, Mehdi Sedighi, Ali Reza Manashty,
published by Journal of Signal and Information Processing, Vol.2 No.2, 2011
has been cited by the following article(s):
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[3] Adaptive Fusion of Sub-band Particle Filters for Robust Tracking of Multiple Objects in Video
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[4] Probabilistic static foreground elimination for background subtraction
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[5] GRADO EN INGENIERÍA DE TECNOLOGÍAS Y SERVICIOS DE TELECOMUNICACIÓN
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[6] A Statistical Background Modeling Algorithm for Real-Time Pixel Classification
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[7] Semitransparency Effect in a Video Using Deep Learning Approach
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[8] Robust tracking of multiple objects in video by adaptive fusion of subband particle filters
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[9] Implementación de un mecanismo de regularización basado en filtros bilaterales para algoritmos de segmentación de objetos móviles
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[10] Multi-scale particle filtering for multiple object tracking in video sequences
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[11] On the Mahalanobis Distance Classification Criterion for a Ventricular Septal Defect Diagnosis System
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[12] Surveillance Video Synopsis Techniques: A Review
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[13] Automated tracking and classification of the settlement behaviour of barnacle cyprids
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[14] Surveillance Video Synopsis Techniques: A Review.
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[15] A novel method for semi transparency effect in academic videos
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[16] Background initialization based on bidirectional analysis and consensus voting
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[17] Moving object detection using scanning camera on a high-precision intelligent holder
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[18] Reasoning on multi-sensor geographic smoke spread data for fire development and risk analysis
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[19] Moving object detection and background enhancement for thalamic visual prostheses
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[20] Motion background modeling based on context-encoder
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[21] Parallel Computer Vision Algorithms for Graphics Processing Units
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[22] Orientation Invariant Autonomous Recognition of Individual Snow Leopards
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[23] Background light ray modeling for change detection
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[24] Finding areas of motion in camera trap images
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[25] Geographic reasoning on multi-modal fire spread data
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[26] A General-Purpose Sensing Floor Architecture for Human-Environment Interaction
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[27] Multi-modal Background Model Initialization
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[28] Estudio e implementación de estrategias de detección de objetos móviles mediante métodos basados en el uso de Local Binary Patterns
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[29] Change detection on light field for active video surveillance
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[30] Robust Subspace Estimation Using Low-Rank Optimization
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[31] Moving Object Detection Using Background Subtraction
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[32] Background and Literature Review
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[33] 彩色视频运动目标自适应在线聚类提取算法
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[34] A Novel Video Dataset for Change Detection Benchmarking
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[35] Robust subspace estimation using low-rank optimization: theory and applications
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[36] A Local Optical Flow Constraint Target Extracting Algorithm of Kalman Filter Based on Background Modeling
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[37] pROST: a smoothed -norm robust online subspace tracking method for background subtraction in video
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[38] A novel video dataset for change detection benchmarking.
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[39] A Fuzzy System for Background Modeling in Video Sequences.
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[40] Object Detection Based on Spatio-temporal Light Field Sensing
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[41] ROBUST SUBSPACE ESTIMATION USING LOW-RANK OPTIMIZATION.
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[42] A Fuzzy System for Background Modeling in Video Sequences
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[43] Improved background modeling for real-time spatio-temporal non-parametric moving object detection strategies
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[44] GPU-based implementation of an optimized nonparametric background modeling for real-time moving object detection
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[45] pROST: A Smoothed Lp-norm Robust Online Subspace Tracking Method for Realtime Background Subtraction in Video
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[46] On the Mahalanobis distance classification criterion for multidimensional normal distributions
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[47] pROST: a smoothed\ ell _p-norm robust online subspace tracking method for background subtraction in video
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[48] Hardware Acceleration of Background Modeling in the Compressed Domain
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[49] 基于DWT 的自适应在线聚类运动目标提取方法
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[50] 基于 DWT 的自适应在线聚类运动目标提取方法
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