Exploiting Features - Locally Interleaved Sequential Alignment for Object Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00212523" target="_blank" >RIV/68407700:21230/13:00212523 - isvavai.cz</a>
Result on the web
<a href="http://cmp.felk.cvut.cz/pub/cmp/articles/hurycd1/hurych-accv2012.pdf" target="_blank" >http://cmp.felk.cvut.cz/pub/cmp/articles/hurycd1/hurych-accv2012.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-37331-2_34" target="_blank" >10.1007/978-3-642-37331-2_34</a>
Alternative languages
Result language
angličtina
Original language name
Exploiting Features - Locally Interleaved Sequential Alignment for Object Detection
Original language description
We exploit image features multiple times in order to make sequential decision process faster and better performing. In the decision process features providing knowledge about the object presence or absence in a given detection window are successively evaluated. We show that these features also provide information about object position within the evaluated window. The classification process is sequentially interleaved with estimating the correct position. The position estimate is used for steering the features yet to be evaluated. This locally interleaved sequential alignment (LISA) allows to run an object detector on sparser grid which speeds up the process. The position alignment is jointly learned with the detector. We achieve a better detection ratesince the method allows for training the detector on perfectly aligned image samples. For estimation of the alignment we propose a learnable regressor that approximates a non-linear regression function and runs in ne2076-1465gligible tim
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Computer Vision - ACCV 2012, 11th Asian Conference on Computer Vision, Part 1
ISBN
978-3-642-37330-5
ISSN
0302-9743
e-ISSN
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Number of pages
14
Pages from-to
446-459
Publisher name
Springer
Place of publication
Heidelberg
Event location
Daejeon
Event date
Nov 5, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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