Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/106973
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical and Electronic Engineering | - |
dc.creator | Li, H | en_US |
dc.creator | Lam, KM | en_US |
dc.creator | Chiu, MY | en_US |
dc.creator | Wu, K | en_US |
dc.creator | Lei, Z | en_US |
dc.date.accessioned | 2024-06-07T00:59:17Z | - |
dc.date.available | 2024-06-07T00:59:17Z | - |
dc.identifier.issn | 1017-9909 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/106973 | - |
dc.language.iso | en | en_US |
dc.publisher | SPIE - International Society for Optical Engineering | en_US |
dc.rights | © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited. | en_US |
dc.rights | The following publication Shandong Dong, Bo Dong, and Changyuan Yu "High sensitivity curvature sensor with a cascaded fiber interferometer", Proc. SPIE 10323, 25th International Conference on Optical Fiber Sensors, 1032372 (23 April 2017) is available at https://doi.org/10.1117/1.JEI.26.5.053024. | en_US |
dc.subject | Cascaded face alignment | en_US |
dc.subject | Intimacy definition feature | en_US |
dc.subject | Random forest | en_US |
dc.title | Cascaded face alignment via intimacy definition feature | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 26 | en_US |
dc.identifier.issue | 5 | en_US |
dc.identifier.doi | 10.1117/1.JEI.26.5.053024 | en_US |
dcterms.abstract | Recent years have witnessed the emerging popularity of regression-based face aligners, which directly learn mappings between facial appearance and shape-increment manifolds. We propose a random-forest based, cascaded regression model for face alignment by using a locally lightweight feature, namely intimacy definition feature. This feature is more discriminative than the pose-indexed feature, more efficient than the histogram of oriented gradients feature and the scale-invariant feature transform feature, and more compact than the local binary feature (LBF). Experimental validation of our algorithm shows that our approach achieves state-of-the-art performance when testing on some challenging datasets. Compared with the LBF-based algorithm, our method achieves about twice the speed, 20% improvement in terms of alignment accuracy and saves an order of magnitude on memory requirement. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Journal of electronic imaging, Sept 2017, v. 26, no. 5, 053024 | en_US |
dcterms.isPartOf | Journal of electronic imaging | en_US |
dcterms.issued | 2017-09 | - |
dc.identifier.scopus | 2-s2.0-85032992621 | - |
dc.identifier.eissn | 1560-229X | en_US |
dc.identifier.artn | 053024 | en_US |
dc.description.validate | 202405 bcch | - |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | EIE-0661 | - |
dc.description.fundingSource | Self-funded | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 6795643 | - |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Lam_Cascaded_Face_Alignment.pdf | Pre-Published version | 1.92 MB | Adobe PDF | View/Open |
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