DocumentCode :
183526
Title :
Verification of family relation from parents and child facial images
Author :
Dandekar, A.R. ; Nimbarte, M.S.
Author_Institution :
Dept. of Comput. Sci. & Eng., RTMNU, Nagpur, India
fYear :
2014
fDate :
6-8 Oct. 2014
Firstpage :
157
Lastpage :
162
Abstract :
There are many social networking web sites used by people and number of photos is uploaded by them. But from photos it is difficult to predict the relationship among the people if necessary. So there is need of system for automatic identification and prediction of relationship among them, specifically kinship from photo. So, we proposed system, which uses Computer Vision, Face recognition, Feature extraction and classification to solve this problem. Proposed System first detects all the features from given photo then extracts them from the faces using Local binary Pattern. Our analysis and psychological studies show that the facial resemblance differs from member to member and depends on image segmentation and image histogram. Implementing the proposed approach on the collected limited family database from Kinface V2 and Family 101 dataset contain child, father and mother images. Our dataset contain family images of Indian celebrities achieved considerable improvement. This computational kinship measurement have a large impact in real applications such as child adoptions, trafficking/smuggling of children, and finding missing children, identifying relatives from a photo collection. So, we empirically evaluate facial representation based on statistical local features, Local Binary Pattern. One can also find classification of the feature, KNN with Euclidean distance find minimum distance from histogram sequence. We observe in our experiments that LBP features perform stably and robustly over a useful range of less resolutions of facial images. We proposed an algorithm to predict the most likely kin relationships embedded in an image from three input images of child, mother and father. In addition, human subjects are used in a baseline study on three databases. Experimental results have shown that the proposed system can effectively annotate the verification of family relation. One way for family (kinship) verification is to perform DNA test that is currently accurate- The DNA test is not suitable for mass screening and a very expensive test for crime scene investigations that takes days to get the results.
Keywords :
computer vision; face recognition; feature extraction; image classification; image representation; image segmentation; image sequences; prediction theory; social networking (online); DNA test; Euclidean distance; Family 101 dataset; KNN; Kinface V2; child facial image; child image; computational kinship measurement; computer vision; crime scene investigations; face recognition; facial representation; facial resemblance; family relation verification; father image; feature classification; feature detection; feature extraction; histogram sequence; image histogram; image segmentation; kin relationship prediction; local binary pattern; mass screening; mother image; parent facial image; relationship identification; social networking Web sites; statistical local features; Accuracy; Databases; Face; Face recognition; Facial features; Feature extraction; Histograms; Face Recognition; Feature Extraction; Kinship Verification; Local Binary Pattern; k-Nearest neighbor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power, Automation and Communication (INPAC), 2014 International Conference on
Conference_Location :
Amravati
Print_ISBN :
978-1-4799-7168-8
Type :
conf
DOI :
10.1109/INPAC.2014.6981146
Filename :
6981146
Link To Document :
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