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
Pedestrian tracking with an infrared sensor using road network information
Download
index.pdf
Date
2012-02-14
Author
Skoglar, Per
Orguner, Umut
Tornqvist, David
Gustafsson, Fredrik
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
206
views
109
downloads
Cite This
This article presents a pedestrian tracking methodology using an infrared sensor for surveillance applications. A distinctive feature of this study compared to the existing pedestrian tracking approaches is that the road network information is utilized for performance enhancement. A multiple model particle filter, which uses two different motion models, is designed for enabling the tracking of both road-constrained (on-road) and unconstrained (off-road) targets. The lateral position of the pedestrians on the walkways are taken into account by a specific on-road target model. The overall framework seamlessly integrates the negative information of occlusion events into the algorithm for which the required modifications are discussed. The resulting algorithm is illustrated on real data from a field trial for different scenarios.
Subject Keywords
Pedestrian tracking
,
Infrared sensor
,
Road network
,
Particle filter
,
Multiple model
,
Occlusion
URI
https://hdl.handle.net/11511/46399
Journal
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
DOI
https://doi.org/10.1186/1687-6180-2012-26
Collections
Department of Electrical and Electronics Engineering, Article
Suggestions
OpenMETU
Core
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...
Road Target Search and Tracking with Gimballed Vision Sensor on an Unmanned Aerial Vehicle
Skoglar, Per; Orguner, Umut; Tornqvist, David; Gustafsson, Fredrik (2012-07-01)
This article considers a sensor management problem where a number of road bounded vehicles are monitored by an unmanned aerial vehicle (UAV) with a gimballed vision sensor. The problem is to keep track of all discovered targets and simultaneously search for new targets by controlling the pointing direction of the vision sensor and the motion of the UAV. A planner based on a state-machine is proposed with three different modes; target tracking, known target search, and new target search. A high-level decisio...
Sensor fusion of a camera and 2D LIDAR for lane detection and tracking
Yeniaydın, Yasin; Schmidt, Klaus Verner; Department of Electrical and Electronics Engineering (2019)
This thesis proposes a novel lane detection and tracking algorithm based on sensor fusion of a camera and 2D LIDAR. The proposed method is based on the top down view of a grayscale image, whose lane pixels are enhanced by the convolution with a 1D top-hat kernel. The convolved image is horizontally divided into a predetermined number of regions and the histogram of each region is computed. Next, the highest valued local maxima in a predefined ratio in the histogram plots are determined as candidate lane pix...
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...
Ferromagnetic Target Detection and Localization with a Wireless Sensor Network
Antepli, Mehmet Akif; Gurbuz, Sevgi Zubeyde; Uysal, Elif (2010-11-03)
This work attempts to address challenges of using magnetic sensors for target detection, localization and tracking with a wireless sensor network (WSN). A WSN comprised of magnetic sensors was constructed to investigate the modeling, detection, and localization of ferrous targets. The system was established as a centralized tree-based wireless network with a PC acting as the fusion center. A heavy cylindrical iron bar was used as a test target and modeled as a magnetic dipole. The magnetic signal models use...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
P. Skoglar, U. Orguner, D. Tornqvist, and F. Gustafsson, “Pedestrian tracking with an infrared sensor using road network information,”
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
, pp. 0–0, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46399.