Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A continuous object tracking system with stationary and moving camera modes
Date
2012-09-27
Author
Emeksiz, Deniz
Temizel, Alptekin
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
228
views
0
downloads
Cite This
Automatic detection and tracking of objects get more important with the increasing number of surveillance cameras and mobile platforms having cameras. Tracking systems are either designed with stationary camera or designed to work in moving camera. When the camera is stationary, correspondence based tracking with background subtraction has a number of benefits such as enabling automatic detection of new objects in the scene and better tracking accuracy. On the other hand, mean shift is a histogram-based tracking method which is suitable for tracking objects under unconstrained scenarios like moving camera. However, with mean shift, the objects to be tracked cannot be detected automatically, only existing or manually selected objects can be tracked. In this paper, we propose a dual-mode system which combines the advantages of correspondence based tracking and mean shift tracking. A reliability measure based on background update rate is calculated for each frame. Under normal operating conditions, when the background estimation is working reliably, correspondence based tracking is used. When the reliability of background estimation becomes low, due to moving camera, the system automatically switches to mean shift tracking until the reliability of background information increases again. The results show that the system can detect new objects and track them reliably using background subtraction. Even though the background subtraction based systems detect high number of false objects when the camera starts moving, the proposed system hands over the tracked objects to mean shift tracker and avoids detection of false objects and enables uninterrupted tracking.
Subject Keywords
Object tracking
,
Moving camera
,
Mean shift
,
Correspondence based tracking
,
Background subtraction
,
Hybrid tracking
URI
https://hdl.handle.net/11511/31986
DOI
https://doi.org/10.1117/12.973720
Collections
Graduate School of Informatics, Conference / Seminar
Suggestions
OpenMETU
Core
Object tracking system with seamless object handover between stationary and moving camera modes
Emeksiz, Deniz; Temizel, Alptekin; Department of Information Systems (2012)
As the number of surveillance cameras and mobile platforms with cameras increases, automated detection and tracking of objects on these systems gain importance. There are various tracking methods designed for stationary or moving cameras. For stationary cameras, correspondence based tracking methods along with background subtraction have various advantages such as enabling detection of object entry and exit in a scene. They also provide robust tracking when the camera is static. However, they fail when the ...
Mean-Shift Tracking for Surveillance Applications Using Thermal and Visible Band Data Fusion
Beyan, Cigdem; Temizel, Alptekin (2011-04-28)
Separate tracking of objects such as people and the luggages they carry is important for video surveillance applications as it would allow making higher level inferences and timely detection of potential threats. However, this is a challenging problem and in the literature, people and objects they carry are tracked as a single object. In this study, we propose using thermal imagery in addition to the visible band imagery for tracking in indoor applications (such as airports, metro or railway stations). We u...
A multimodal approach for individual tracking of people and their belongings
Beyan, Çiğdem; Temizel, Alptekin (2015-04-01)
In this study, a fully automatic surveillance system for indoor environments which is capable of tracking multiple objects using both visible and thermal band images is proposed. These two modalities are fused to track people and the objects they carry separately using their heat signatures and the owners of the belongings are determined. Fusion of complementary information from different modalities (for example, thermal images are not affected by shadows and there is no thermal reflection or halo effect in...
Evaluation of deep learning based multiple object trackers
Moured, Omar; Akar, Gözde; Department of Electrical and Electronics Engineering (2020-9)
Multiple object tracking (MOT) is a significant problem in the computer vision community due to its applications, including but not limited to, surveillance and emerging autonomous vehicles. The difficulties of this problem lie in several challenges, such as frequent occlusion, interaction, intra-class variations, in-and-out objects, etc. Recently, deep learning MOT methods confront these challenges effectively. State-of-the-art deep learning (DL) trackers pipeline consists of two stages, i.e., appearance h...
A Reliable and Reversible Image Privacy Protection Based on False Colors
ÇİFTÇİ, Serdar; Akyüz, Ahmet Oğuz; Ebrahimi, Touradj (2018-01-01)
Protection of visual privacy has become an indispensable component of video surveillance systems due to pervasive use of video cameras for surveillance purposes. In this paper, we propose two fully reversible privacy protection schemes implemented within the JPEG architecture. In both schemes, privacy protection is accomplished by using false colors with the first scheme being adaptable to other privacy protection filters while the second is false color-specific. Both schemes support either a lossless mode ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
D. Emeksiz and A. Temizel, “A continuous object tracking system with stationary and moving camera modes,” 2012, vol. 8541, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/31986.