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Static Object Detection Based on a Dual Background Model and a Finite-State Machine

Rubén Heras Evangelio, Thomas Sikora
2011 EURASIP Journal on Image and Video Processing  
Based on the detection of two background models learning at different rates, pixels are classified with the help of a finite-state machine.  ...  In this paper, we present a system for the detection of static objects in crowded scenes.  ...  To solve the problem that poses static objects concerning the updating of the long-term background model in dual background systems, we propose a system that, based on the results obtained from a dual  ... 
doi:10.1155/2011/858502 fatcat:xms4tcupbvfend6sk3pxqadnqe

Abandoned Object Detection using Temporal Consistency Modeling

Divya C., Pravin S.
2017 International Journal of Computer Applications  
Keywords Abandoned object detection, long-term background model, short-term background model, visual surveillance, pixel based finite state machine, image processing.  ...  To identify the static foreground regions, a framework is used based on the temporal transition of code pattern and it also determines whether the candidate regions contain the abandoned object by analyzing  ...  Here a simple pixel-based finite state machine (PFSM) models introduced, which uses temporal transition information.  ... 
doi:10.5120/ijca2017913707 fatcat:didh6r5tava2dik3xf7haum3yq

Detection of Stationary Foreground Objects Using Multiple Nonparametric Background-Foreground Models on a Finite State Machine

Carlos Cuevas, Raquel Martinez, Daniel Berjon, Narciso Garcia
2017 IEEE Transactions on Image Processing  
The results of the detectors are fed into a novel finite state machine that classifies the pixels among background, moving foreground objects, stationary foreground objects, occluded stationary foreground  ...  This paper presents an efficient and highquality strategy to detect stationary foreground objects, which is able to detect not only completely static objects but also partially static ones.  ...  First, a robust foreground detection using KDE-based nonparametric background and foreground models is performed. Then, an efficient FSM is used to determine which foreground objects remain static.  ... 
doi:10.1109/tip.2016.2642779 pmid:28026761 fatcat:b5pkrsynrbeflesyxcau62z3ra

Abandoned Object Detection via Temporal Consistency Modeling and Back-Tracing Verification for Visual Surveillance

Miss. Komal Sunil Patil, Prof. Girish A. Kulkarni
2018 IARJSET  
We introduce an abandoned object detection tool based on a set of possible events and on a set of rules to act upon those events.  ...  Abandoned object detection is an essential requirement in many video surveillance contexts.  ...  A pixel is associated with only one state at a time. Based on long-and short-term background models, the state of pixel i can be changed from one state at time t to another state at time t + 1.  ... 
doi:10.17148/iarjset.2018.592 fatcat:lu4zh42tyna6noeudwtem7ld54

Abandoned Object Detection via Temporal Consistency Modeling and Back-Tracing Verification for Visual Surveillance

Kevin Lin, Shen-Chi Chen, Chu-Song Chen, Daw-Tung Lin, Yi-Ping Hung
2015 IEEE Transactions on Information Forensics and Security  
Index Terms-Abandoned luggage detection, abandoned object detection, short-term background model, long-term background model, object detection and tracking, visual surveillance.  ...  Subsequently, we introduce a framework to identify static foreground regions based on the temporal transition of code patterns, and to determine whether the candidate regions contain abandoned objects  ...  Subsequently, we introduce a simple pixel-based finite-state machine (PFSM) model that uses temporal transition information to identify the static foreground based on the sequence pattern of each object  ... 
doi:10.1109/tifs.2015.2408263 fatcat:bpibsjj77zdfbluuytitzb666i

Static object detection and segmentation in videos based on dual foregrounds difference with noise filtering [article]

Waqqas-ur-Rehman Butt, Martin Servin
2020 arXiv   pre-print
In this context, background subtraction technique based on the frame difference concept is applied to the identification of static objects.  ...  This paper presents static object detection and segmentation method in videos from cluttered scenes.  ...  The authors are thankful to Boliden AB for providing data and to Daniel Lindmark at Umeå University for assistance with producing the synthetic data.  ... 
arXiv:2012.10708v1 fatcat:jpxe6pjwunb5tdeprfo6jr2qza

Abandoned Object Detection Using Dual Background Model from Surveillance Videos

Purvi Bhandari, Tushar Ratanpara, Dr.Wandra K.H
2017 International Journal of Engineering and Technology  
The proposed system is used todetect the abandoned object from the surveillance videos with the use of dual background model. The division of video into frames is done and are pre-processed.  ...  The foreground blobs are generated using subtraction of the two backgrounds and it is tracked to detect the abandoned objects.  ...  Subsequently, method introduced a simple pixel-based finite-state machine (PFSM) model that is used to temporal transition information to identify the static foreground based on the sequence pattern of  ... 
doi:10.21817/ijet/2017/v9i3/170903s034 fatcat:rportyvwkvfhnc5jle6tkr54s4

A Consistent Two-Level Metric For Evaluation Of Automated Abandoned Object Detection Methods

Patrick Krusch, Erik Bochinski, Volker Eiselein, Thomas Sikora
2017 Zenodo  
Therefore and due to benchmarks with commonly only few abandoned objects and a non-standardized evaluation procedure, an objective performance comparison between different methods is generally hard.  ...  Scientific interest in automated abandoned object detection algorithms using visual information is high and many related systems have been published in recent years.  ...  ACKNOWLEDGEMENTS The research leading to these results has received funding from the European Communitys FP7 and BMBF-VIP+ under grant agreement number 607480 (LASIE) and 03VP01940 (SiGroViD).  ... 
doi:10.5281/zenodo.1078507 fatcat:iw5en2f3m5bsbppgospuevlnce

Model for Object Detection using Computer Vision and Machine Learning for Decision Making

Aditya Raj, Manish Kannaujiya, Ajeet Bharti, Rahul Prasad, Namrata Singh, Ishan Bhardwaj
2019 International Journal of Computer Applications  
This paper gives the efficient model of the process of detecting the object and analyzing the gesture of an object using the machine learning and computer vision for decision making after surveying various  ...  research in the field of pattern recognition.* It is based on the objects behavioural activities, Gesture recognition is very essential for making a decision.  ...  The state of this system can be illustrated as a finite state machine ( FSM). There are a total of a six system states. The states depend on the no. And the type of finger detected.  ... 
doi:10.5120/ijca2019918516 fatcat:n3mwrq4n7nfnlip5q4qth3ztuu

Stationary foreground detection for video-surveillance based on foreground and motion history images

Diego Ortego, Juan C. SanMiguel
2013 2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance  
In this paper, we propose an approach for stationary foreground detection in video based on the spatio-temporal variation of foreground and motion data.  ...  Foreground data are obtained by Background Subtraction to detect regions of interest.  ...  They can be extended by defining the states of foreground pixels through finite-state-machines such as for GMMs [14] and dual-backgrounds [8] .  ... 
doi:10.1109/avss.2013.6636619 dblp:conf/avss/OrtegoS13 fatcat:o66m42cwd5henl4ciq56ul3bni

Computer Vision based System to Detect Abandoned Objects

2019 International Journal of Engineering and Advanced Technology  
This paper is focused towards developing a computer vision based approach that analyses the blob areas to detect any abandoned objects and instantaneously send appropriate alert without any human intervention  ...  One of the impending threats to security in crowded places is the ignorance of un-attended objects.  ...  ACKNOWLEDGMENT The authors wish to express their thanks the people involved in creating the ABODA dataset which has been used as part of this experiment in detecting abandoned objects.  ... 
doi:10.35940/ijeat.a1095.109119 fatcat:43fuvjxoejcbro7hv6j7qazssq

Camera-Based Light Emitter Localization Using Correlation of Optical Pilot Sequences

Md Rashed Rahman, T. V. Sethuraman, Marco Gruteser, Kristin J. Dana, Shubham Jain, Narayan B. Mandayam, Ashwin Ashok
2022 IEEE Access  
detection, support-vector machine based (SVM) machine learning, and you only look once (YOLO), which is a state-of-the-art convolutional neural network (CNN) deep learning based object identification  ...  Visual identification of objects using cameras requires precise detection, localization, and recognition of the objects in the field-of-view.  ...  ACKNOWLEDGMENT The authors would like to thank Hansi Liu (Rutgers), Abrar Ali (Old Dominion University), and Abbaas Nishar (Georgia State University), for their valuable inputs to improve the quality of  ... 
doi:10.1109/access.2022.3153708 fatcat:yqyval75ebgybn2oeopqqq2vyu

A Framework for Real-Time Physical Human-Robot Interaction using Hand Gestures

Osama Mazhar, Sofiane Ramdani, Benjamin Navarro, Robin Passama, Robin Passama
2018 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO)  
A physical Human-Robot Interaction (pHRI) framework is proposed using vision and force sensors for a two-way object hand-over task.  ...  This will be extended for the development of intelligent human intention detection in pHRI scenarios to efficiently recognize a variety of static as well as dynamic gestures.  ...  We realize a tool (here, a portable screw-driver) handover experiment, guided by a finite state machine designed for the robot control.  ... 
doi:10.1109/arso.2018.8625753 dblp:conf/arso/MazharRNPP18 fatcat:6llxepwpejfv5fp5ltjmjddceq

Survey on Vehicle Detection and Tracking Techniques in Video Surveillance

Swathy M., Nirmala P., Geethu P.
2017 International Journal of Computer Applications  
A new 3D model-based vehicle detection framework is based on a probabilistic boundary feature grouping, used for vehicle tracking and detection.This framework supported advantageous characteristics such  ...  Here this model is limitation is addressed with a second model, that is based on a Bayesian treatment of Poisson regression that introduces a preceding distribution on the linear weights of the model.  ... 
doi:10.5120/ijca2017913086 fatcat:yq22nc2xqfca7krq5hudfhbrwy

Human Behavior Recognition in Shopping Settings

Ronan Sicre, Henri Nicolas
2015 IPSJ Transactions on Computer Vision and Applications  
Specifically, the system is divided in three parts: low-level, mid-level, and high-level analysis. Low-level analysis detects and tracks moving object in the scene.  ...  Specifically, the system detects customer interests and interactions with various products at a point of sale.  ...  Finite State Machine A finite state machine is used to organize and prioritize the eight states [7] , [45] . The state machine is synchronous and deterministic.  ... 
doi:10.2197/ipsjtcva.7.151 fatcat:ao7vsh3qwbb2hhmoz3n4kmvyue
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