Overview / Usage

The recent growth in social media and the social platform has given rise to increasing amount of application. The automatic classification of age and gender has become relevant for an increasing request of applications. The performance which is reports for the related task of face recognition, the performance of current methods on real-world images is lacking considerably.

Age detection plays a key role in many fields like Multimedia Retrieval and Human-Machine Interaction. Vocabulary used to address people changes according to the age groups very often. Gender Identification is one of the major components for developing gender-dependent acoustic modules for speech recognition etc. Salutations and grammar rules of languages vary from one gender to the other.

Input: Face of a person
Output: Age and gender group for the input image

Scope: classification into respective age group (rather than regression) and gender.

Methodology / Approach

Using 5 layered Convolutional Neural network.

Technologies Used

openCV

openVINO

oneAPI

TensorFlow