summaryrefslogtreecommitdiff
path: root/scraper/datasets/scholar/entries/Localizing Parts of Faces Using a Consensus of Exemplars.csv
diff options
context:
space:
mode:
authoradamhrv <adam@ahprojects.com>2018-12-15 19:57:49 +0100
committeradamhrv <adam@ahprojects.com>2018-12-15 19:57:49 +0100
commit82b2c0b5d6d7baccbe4d574d96e18fe2078047d7 (patch)
treea8784b7ec2bc5a0451c252f66a6b786f3a2504f5 /scraper/datasets/scholar/entries/Localizing Parts of Faces Using a Consensus of Exemplars.csv
parent8e978af21c2b29f678a09701afb3ec7d65d0a6ab (diff)
parentc5b02ffab8d388e8a2925e51736b902a48a95e71 (diff)
Merge branch 'master' of github.com:adamhrv/megapixels_dev
Diffstat (limited to 'scraper/datasets/scholar/entries/Localizing Parts of Faces Using a Consensus of Exemplars.csv')
-rw-r--r--scraper/datasets/scholar/entries/Localizing Parts of Faces Using a Consensus of Exemplars.csv1
1 files changed, 1 insertions, 0 deletions
diff --git a/scraper/datasets/scholar/entries/Localizing Parts of Faces Using a Consensus of Exemplars.csv b/scraper/datasets/scholar/entries/Localizing Parts of Faces Using a Consensus of Exemplars.csv
new file mode 100644
index 00000000..0fa7a800
--- /dev/null
+++ b/scraper/datasets/scholar/entries/Localizing Parts of Faces Using a Consensus of Exemplars.csv
@@ -0,0 +1 @@
+Localizing parts of faces using a consensus of exemplars|http://scholar.google.com/https://ieeexplore.ieee.org/abstract/document/6412675/|2013|740|13|8801930631236620204|None|http://scholar.google.com/scholar?cites=8801930631236620204&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=8801930631236620204&hl=en&as_sdt=0,5|None|We present a novel approach to localizing parts in images of human faces. The approach combines the output of local detectors with a nonparametric set of global models for the part locations based on over 1,000 hand-labeled exemplar images. By assuming that the global models generate the part locations as hidden variables, we derive a Bayesian objective function. This function is optimized using a consensus of models for these hidden variables. The resulting localizer handles a much wider range of expression, pose, lighting, and …