2014
DOI: 10.7763/ijcce.2014.v3.301
|View full text |Cite
|
Sign up to set email alerts
|

Gender Classification Based on Binary Haar Cascade

Abstract: Gender classification is a difficult but also an essential task under the researches of pattern recognition. There are several methods and features used for this task such as face, gait, or full body features. One of the most widely used techniques is Haar cascades. Default Haar features based classifiers can only detect pedestrian, free from gender information. In this paper we aimed to learn the gender of the target pedestrians by Haar cascades that are trained gender specific. We trained the classifier with… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

2015
2015
2021
2021

Publication Types

Select...
3
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(3 citation statements)
references
References 9 publications
(10 reference statements)
0
3
0
Order By: Relevance
“…To do this, PIANO automatically calculates the size of each section. [13] It relies on the same algorithm used from Haar Cascades [33], and like them, the classifier of this tracker is trained online during execution.…”
Section: Mapping Space To Soundmentioning
confidence: 99%
“…To do this, PIANO automatically calculates the size of each section. [13] It relies on the same algorithm used from Haar Cascades [33], and like them, the classifier of this tracker is trained online during execution.…”
Section: Mapping Space To Soundmentioning
confidence: 99%
“…Two or three adjacent rectangular groups with different contrast values create Haar-like features [5]. The intensity values of white and black groups are separately calculated and subtracted from each other.…”
Section: Detection Based On Haar-like Featurementioning
confidence: 99%
“…The calculated distances and ratios are used to identify the images and classify them [2]. Mustafa et al [1] used a simple method by detecting a region of interest(ROI) by assigning positive to the facial images and negative to other areas in a still image. This way, it becomes a simple binary problem.…”
Section: Literature Survey a Binary Classification Using Haar Camentioning
confidence: 99%