NDLI: Real-time abandoned and stolen object detection based on spatio-temporal features in crowded scenes

Content Provider	Springer Nature Link
Author	Nam, Yunyoung
Copyright Year	2015
Abstract	Abandoned and stolen object detection is a challenging task due to occlusion, changes in lighting, large perspective distortion, and the similarity in appearance of different people. This paper presents real-time detection methods of abandoned and stolen objects in a complex video. The adaptive background modeling method is applied to stable tracking and the ghost image removing. To detect abandoned and stolen objects, the methods determine spatio-temporal relationship between moving people and suspicious drops. The space first detection method measures the distance between a moving object and a non-moving object in spatial change analysis. The time first detection method conducts temporal change analysis and then spatial change analysis. The potential abandoned object is classified as a definite abandoned or stolen object by two-level detection approach. The time-to-live timer is applied by adjusting several key parameters on each camera and environment. In experiments, we show the experimental results to evaluate our proposed methods using benchmark datasets.
Starting Page	7003
Ending Page	7028
Page Count	26
File Format	PDF
ISSN	13807501
Journal	Multimedia Tools and Applications
Volume Number	75
Issue Number	12
e-ISSN	15737721
Language	English
Publisher	Springer US
Publisher Date	2015-04-30
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Abandoned object Stolen object Left object Background subtraction Video surveillance Multimedia Information Systems Computer Communication Networks Data Structures, Cryptology and Information Theory Special Purpose and Application-Based Systems
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Hardware and Architecture Software Media Technology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Video surveillance system based on a scalable application-oriented architecture

Spatio-Temporal Tube data representation and Kernel design for SVM-based video object retrieval system

Loitering detection using an associating pedestrian tracker in crowded scenes

Background modeling and its evaluation for complex scenes

Object segmentation and key-pose based summarization for motion video

Crowd flux analysis and abnormal event detection in unstructured and structured scenes

Evaluation of multiple features for violent scenes detection

Intelligent video surveillance system: 3-tier context-aware surveillance system with metadata

On line background modeling for moving object segmentation in dynamic scenes

Real-time abandoned and stolen object detection based on spatio-temporal features in crowded scenes

Similar Documents

Video surveillance system based on a scalable application-oriented architecture

Spatio-Temporal Tube data representation and Kernel design for SVM-based video object retrieval system

Loitering detection using an associating pedestrian tracker in crowded scenes

Background modeling and its evaluation for complex scenes

Object segmentation and key-pose based summarization for motion video

Crowd flux analysis and abnormal event detection in unstructured and structured scenes

Evaluation of multiple features for violent scenes detection

Intelligent video surveillance system: 3-tier context-aware surveillance system with metadata

On line background modeling for moving object segmentation in dynamic scenes

Real-time abandoned and stolen object detection based on spatio-temporal features in crowded scenes