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Jaswal, Gagandeep
- Score Calibration in Face Acknowledgement
Abstract Views :148 |
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Authors
Affiliations
1 Electronics and Communication Engineering Department, Punjabi University, Patiala, IN
1 Electronics and Communication Engineering Department, Punjabi University, Patiala, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 18, No 1 (2016), Pagination: 1-15Abstract
An appraisal of the confirmation and adjustment execution of a face acknowledgment frameworks are needy upon inter session variability (ISV) demonstrating is displayed. As an option to adjustment through direct change of scores, downright alignment is acquainted as an approach to contain extra data about pictures for adjustment. The expense of probability proportion, which is a surely understood border in the speaker acknowledgment field, is utilized as an adjustment execution parameter. The outcomes accomplished from the testing web camera face databases indicate that directly aligned face acknowledgment scores are less vague in their probability proportion understanding than unadjusted scores. Furthermore, the clear cut alignment tests exhibit that adjustment can be used not just to improve the probability proportion understanding of scores, additionally to build the confirmation execution of the face acknowledgment frameworks.Full Text
- A Review Paper on Face Recognition Techniques
Abstract Views :211 |
PDF Views:5
Authors
Affiliations
1 Punjabi University, Patiala, IN
1 Punjabi University, Patiala, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 17, No 1 (2016), Pagination: 127-133Abstract
Face recognition presents a challenging problem in the process of image analysis and computer vision. Face recognition techniques can be broadly classified into three categories based on the face data acquisition methodology: methods that operates on intensity images; those that deal with video sequences; and those that requires other sensory data such as 3D information or infra-red imagery. High data dimensionality makes it challenging to distinguish the required discriminative information. In this paper, an overview of some well-known dimension reduction techniques is presented and some of the benefits and drawbacks of the schemes mentioned therein are examined. This paper also mentions the classification of dimension reduction techniques being developed and tries to give an idea of the state of the art of face recognition technology.Keywords
Face Recognition, Image Analysis, Data Acquisition, Dimension Reduction Techniques.Full Text