We proposed a novel framework for video content understanding that uses rules constructed from knowledge bases and multimedia ontologies. Our framework consists of an expert system that uses a rule-based engine, domain knowledge, visual detectors (for objects and scenes), and metadata (text from automatic speech recognition, related text, etc.). We introduce the idea of modal keywords, which ar...

This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process...

his paper reviews Biometric based Speaker Recognition and presents brief about various algorithms and techniques used at various stages of Speaker Recognition and development of Attendance System as application of Speaker Recognition. The research is being carried out in this area for many years. However, the accuracy of system depends upon speaker’s variability and environmental conditions. Va...

Biometrics methods include recognition techniques such as fingerprint, iris, hand geometry, voice, face, ears and gait. The gait recognition approach has some advantages, for example it does not need the prior concern of the observed subject and it can record many biometric features in order to make deeper analysis, but most of the research proposals use high computational cost. This paper show...

The aim of this paper is a comparative analysis of methods for motion detection and human recognition in the image. Authors propose the own solution following the comparative analysis of current approaches. Then authors design and implement hardware and software solution for motion detection in the video with human recognition in the picture. The development board Intel Galileo serves as the ba...

In face recognition, feature extraction techniques attempts to search for appropriate representation of the data. However, when the feature dimension is larger than the samples size, it brings performance degradation. Hence, we propose a method called Normalization Discriminant Independent Component Analysis (NDICA). The input data will be regularized to obtain the most reliable features from t...

Face recognition has advantages over other biometric methods. Principal Component Analysis (PCA) has been widely used for the face recognition algorithm. PCA has limitations such as poor discriminatory power and large computational load. Due to these limitations of the existing PCA based approach, we used a method of applying PCA on wavelet subband of the face image and two methods are proposed...