Reduced Search Space for Rapid Bicycle Detection
Ardö, Håkan LU ; Nilsson, Mikael LU ; Laureshyn, Aliaksei LU
and Persson, Anna
LU
(2013)
2nd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2013)
- Abstract
- This paper describes a solution to the application of rapid detection of bicycles in low resolution video. In
particular, the application addressed is from video recorded in a live environment. The future aim from the
results in this paper is to investigate a full year of video data. Hence, processing speed is of great concern.
The proposed solution involves the use of an object detector and a search space reduction method based on
prior knowledge regarding the application at hand. The method using prior knowledge utilizes random sample
consensus, and additional statistical analysis on detection outputs, in order to define a reduced search space. It
is experimentally shown that, in the... (More) - This paper describes a solution to the application of rapid detection of bicycles in low resolution video. In
particular, the application addressed is from video recorded in a live environment. The future aim from the
results in this paper is to investigate a full year of video data. Hence, processing speed is of great concern.
The proposed solution involves the use of an object detector and a search space reduction method based on
prior knowledge regarding the application at hand. The method using prior knowledge utilizes random sample
consensus, and additional statistical analysis on detection outputs, in order to define a reduced search space. It
is experimentally shown that, in the application addressed, it is possible to reduce the full search space by 62%
with the proposed methodology. This approach, which employs a full detector in combination with the design
of a simple and fast model that can capture prior knowledge for a specific application, leads to a reduced search
space and thereby a significantly improved processing speed. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3294728
- author
- Ardö, Håkan
LU
; Nilsson, Mikael
LU
; Laureshyn, Aliaksei
LU
and Persson, Anna
LU
- organization
- publishing date
- 2013
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Bicycle Detection, Search Space, RANSAC, SMQT, split up SNoW
- host publication
- [Host publication title missing]
- pages
- 6 pages
- publisher
- SciTePress
- conference name
- 2nd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2013)
- conference location
- Barcelona, Spain
- conference dates
- 2013-02-15 - 2013-02-18
- external identifiers
-
- scopus:84877948121
- DOI
- 10.5220/0004264804530458
- language
- English
- LU publication?
- yes
- id
- c39e94c9-151d-443b-933d-ce748871efd4 (old id 3294728)
- date added to LUP
- 2016-04-04 11:06:16
- date last changed
- 2022-01-29 21:20:12
@inproceedings{c39e94c9-151d-443b-933d-ce748871efd4,
abstract = {{This paper describes a solution to the application of rapid detection of bicycles in low resolution video. In<br/><br>
particular, the application addressed is from video recorded in a live environment. The future aim from the<br/><br>
results in this paper is to investigate a full year of video data. Hence, processing speed is of great concern.<br/><br>
The proposed solution involves the use of an object detector and a search space reduction method based on<br/><br>
prior knowledge regarding the application at hand. The method using prior knowledge utilizes random sample<br/><br>
consensus, and additional statistical analysis on detection outputs, in order to define a reduced search space. It<br/><br>
is experimentally shown that, in the application addressed, it is possible to reduce the full search space by 62%<br/><br>
with the proposed methodology. This approach, which employs a full detector in combination with the design<br/><br>
of a simple and fast model that can capture prior knowledge for a specific application, leads to a reduced search<br/><br>
space and thereby a significantly improved processing speed.}},
author = {{Ardö, Håkan and Nilsson, Mikael and Laureshyn, Aliaksei and Persson, Anna}},
booktitle = {{[Host publication title missing]}},
keywords = {{Bicycle Detection; Search Space; RANSAC; SMQT; split up SNoW}},
language = {{eng}},
publisher = {{SciTePress}},
title = {{Reduced Search Space for Rapid Bicycle Detection}},
url = {{http://dx.doi.org/10.5220/0004264804530458}},
doi = {{10.5220/0004264804530458}},
year = {{2013}},
}