samy.bakheet

Dr.-Ing. Samy Bakheet

Assistant Professor - Neuro-Information Technology

Faculty of Computers and Information

Address: P. O. Box 82524 Sohag, Egypt

1357

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Publications Which contain the keyword: video interpretation


Hand gesture recognition using optimized local gabor feature
Since a bank of 2D Gabor filters has a large potential to isolate texture according to particular frequencies and orientations, the usage of Gabor features to simulate the visual features extracted from human hand is a very effective way. In this paper, we propose an optimized Gabor features based framework for real-time hand gesture recognition explicitly targeted to depth data. ... Read more

A fuzzy framework for real-time gesture spotting and recognition
A vital requirement of any recognition system claiming to be real time is the capability to perform feature extraction in real time. In this paper, we propose an innovative fuzzy approach for real-time dynamic gesture recognition and spotting, where a compact local descriptor is designed to model moving gesture skeletons as a time series of fuzzy statistical features. Then, a ... Read more

Gesture recognition using optimized gabor features
Since a bank of 2D Gabor filters has a large potential to isolate texture according to particular frequencies and orientations, the usage of Gabor features to simulate the visual features extracted from human hand is a very effective way. In this paper, we propose an optimized Gabor features based framework for real-time hand gesture recognition explicitly targeted to depth data. ... Read more

Video-Based Recognition and Representation of Human Actions
Our primary concern in this book is to explore and establish theories and methodologies for accurate representation and recognition of human actions in video data. Throughout the chapters of the book, several approaches involving diverse conceptualizations are presented to represent and recognize human actions from video sequences. Moreover, in Chapter 4, a variety of distinctive visual features (shape and motion ... Read more

Human activity recognition: A scheme using multiple cues
In this work, a schematic model for human activity recognition based on multiple cues is introduced. In the beginning, a sequence of temporal silhouettes of the moving human body parts are extracted from a video clip (i.e., an action snippet). Next, each action snippet is temporally split into several time-slices represented by fuzzy intervals. As shape features, a variety of ... Read more

A Fast Statistical Approach for Human Activity Recognition
An essential part of any activity recognition system claiming be truly real-time is the ability to perform feature extrac- tion in real-time. We present, in this paper, a quite simple and computationally tractable approach for real-time human activity recognition that is based on simple statistical features. These features are simple and relatively small, accord- ingly they are easy and fast ... Read more

Toward Robust Action Retrieval in Video
Retrieving human actions from video databases is a paramount but challenging task in computer vision. In this work, we develop such a framework for robustly recognizing human actions in video sequences. The contribution of the paper is twofold. First a reliable neural model, the Multi-level Sigmoidal Neural Network (MSNN) as a classifier for the task of action recognition is presented. ... Read more

Toward real-world activity recognition: An SVM based system using fuzzy directional features
Despite their attractive properties of invariance, robustness and reliability, fuzzy directional features are not hitherto paid the attention they deserve in the activity recognition literature. In this paper, we propose to adopt an innovative approach for activity recognition in real-world scenes, where a new fuzzy motion descriptor is developed to model activities as time series of fuzzy directional features. A ... Read more

Recognition of Human Actions Based on Temporal Motion Templates
Despite their attractive properties of invariance, robustness and reliability, statistical motion descriptions from temporal templates have not apparently received the amount of attention they might deserve in the human action recognition literature. In this paper, we propose an innovative approach for action recognition, where a novel fuzzy representation based on temporal motion templates is developed to model human actions as ... Read more