A Temporal-Spatial Method for Group Detection, Locating and Tracking
With the prevalence of smart devices, such as smart phones, wearable equipments, and infrastructures, location-based service (LBS) has thrived in our daily life. In those practical LBS applications, group detection and tracking is a context-related research field in many scenarios, such as school ya...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2016-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/7549033/ |
id |
doaj-c6de449f65ca426c869efa34a18bd67a |
---|---|
record_format |
Article |
spelling |
doaj-c6de449f65ca426c869efa34a18bd67a2021-03-29T19:39:46ZengIEEEIEEE Access2169-35362016-01-0144484449410.1109/ACCESS.2016.26006237549033A Temporal-Spatial Method for Group Detection, Locating and TrackingShengnan Li0https://orcid.org/0000-0001-5499-6059Zheng Qin1Houbing Song2https://orcid.org/0000-0003-2631-9223School of Software and TNList, Tsinghua University, Beijing, ChinaSchool of Software and TNList, Tsinghua University, Beijing, ChinaDepartment of Electrical and Computer Engineering, West Virginia University, Montgomery, WV, USAWith the prevalence of smart devices, such as smart phones, wearable equipments, and infrastructures, location-based service (LBS) has thrived in our daily life. In those practical LBS applications, group detection and tracking is a context-related research field in many scenarios, such as school yard, office building, shopping mall and so on. In this paper, we heuristically develop a temporal-spatial method for clustering and locating the groups, and then leverage a CRF-based event detection mechanism to improve the performance of recognizing contextual behaviors. The experimental results demonstrate that our system can achieve an impressive accuracy and precision of grouping and tracking.https://ieeexplore.ieee.org/document/7549033/Internet of Thingsgroup detectiontemporal-spatialsmart computing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shengnan Li Zheng Qin Houbing Song |
spellingShingle |
Shengnan Li Zheng Qin Houbing Song A Temporal-Spatial Method for Group Detection, Locating and Tracking IEEE Access Internet of Things group detection temporal-spatial smart computing |
author_facet |
Shengnan Li Zheng Qin Houbing Song |
author_sort |
Shengnan Li |
title |
A Temporal-Spatial Method for Group Detection, Locating and Tracking |
title_short |
A Temporal-Spatial Method for Group Detection, Locating and Tracking |
title_full |
A Temporal-Spatial Method for Group Detection, Locating and Tracking |
title_fullStr |
A Temporal-Spatial Method for Group Detection, Locating and Tracking |
title_full_unstemmed |
A Temporal-Spatial Method for Group Detection, Locating and Tracking |
title_sort |
temporal-spatial method for group detection, locating and tracking |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2016-01-01 |
description |
With the prevalence of smart devices, such as smart phones, wearable equipments, and infrastructures, location-based service (LBS) has thrived in our daily life. In those practical LBS applications, group detection and tracking is a context-related research field in many scenarios, such as school yard, office building, shopping mall and so on. In this paper, we heuristically develop a temporal-spatial method for clustering and locating the groups, and then leverage a CRF-based event detection mechanism to improve the performance of recognizing contextual behaviors. The experimental results demonstrate that our system can achieve an impressive accuracy and precision of grouping and tracking. |
topic |
Internet of Things group detection temporal-spatial smart computing |
url |
https://ieeexplore.ieee.org/document/7549033/ |
work_keys_str_mv |
AT shengnanli atemporalspatialmethodforgroupdetectionlocatingandtracking AT zhengqin atemporalspatialmethodforgroupdetectionlocatingandtracking AT houbingsong atemporalspatialmethodforgroupdetectionlocatingandtracking AT shengnanli temporalspatialmethodforgroupdetectionlocatingandtracking AT zhengqin temporalspatialmethodforgroupdetectionlocatingandtracking AT houbingsong temporalspatialmethodforgroupdetectionlocatingandtracking |
_version_ |
1724195875515793408 |