Dynamic multi-attribute priority based face attribute detection for robust face image retrieval system
- PDF / 4,359,150 Bytes
- 25 Pages / 439.37 x 666.142 pts Page_size
- 4 Downloads / 222 Views
Dynamic multi-attribute priority based face attribute detection for robust face image retrieval system S. Suchitra 1
& R. J. Poovaraghan
2
Received: 25 April 2019 / Revised: 4 June 2020 / Accepted: 15 June 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
The increase in the popularity of social websites and smartphones has helped people to easily click photos and upload them on the internet. Almost 60% of the photos are human faces. There might be an increase in face search in future because human faces are closely associated with social media where people show special interest on specific personalities. The main issue raised in the face retrieval system is the various intra-class variances like expression, pose and illumination. Most of the conventional approaches lack the accuracy to meet the human intuition for retrieving images. The proposed approach develops a Dynamic Multi-Attribute Priority-based Face Attribute Detection (DMAP-FAD) method based on contextual information of the face (Race and Gender) by detecting the attributes dynamically. This approach can provide better discrimination of the face image retrieval system by detecting the attributes dynamically. The digital binning technique is applied for improving the lighting differences for illumination. The proposed method effectively minimized the semantic gap and achieved high accuracy by focusing on the variations involved in the pose, illumination, and expression with dynamically detected an optimal set of attributes from the original set of attributes by using contextual relationship. In the experimental results, the proposed method has been tested efficiently by the metrics such as F-Score, Precision and Recall with help of Pubfig and LFW datasets and it is observed that the proposed method obtained an overall accuracy of 95.63% for higher discrimination of face image retrieval system. The results are comparable with those of the state-ofthe-art methods. Keywords Face image retrieval . DMAP-FAD . Multiple face attributes . Sparse Codewords . Indexing
* S. Suchitra [email protected]
1
Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India
2
Department of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
Multimedia Tools and Applications
1 Inroduction The substantial growth of optical instruments like mobile phones and camera facilitate people to capture every moment of their life as a photo and upload the same on the internet by using different on-line platforms like Facebook, Twitter, Quicker, Flicker, etc. Among all these digital photos and images shared on the net, a great percentage of the photos are associated with human faces. As a result of human faces are strongly associated with the social activities of individuals. Having a wide range of photos of a particular person’s interest may increase the need for face search. The continuous development of facial images has produced several research problems and
Data Loading...
