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Full-Text Articles in Physical Sciences and Mathematics
Fuzzy Logic-Based Image Fusion For Multi-View Through-The-Wall Radar, Cher Hau Seng, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Moeness G. Amin
Fuzzy Logic-Based Image Fusion For Multi-View Through-The-Wall Radar, Cher Hau Seng, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Moeness G. Amin
Dr Fok Hing Chi Tivive
In this paper, we propose a new technique for image fusion in multi-view through-the-wall radar imaging system. As most existing image fusion methods for through-the-wall radar imaging only consider a global fusion operator, it is desirable to consider the differences between each pixel using a local operator. Here, we present a fuzzy logic-based method for pixel-wise image fusion. The performance of the proposed method is evaluated on both simulated and real data from through-the-wall radar imaging system. Experimental results show that the proposed method yields improved performance, compared to existing methods.
A Gender Recognition System Using Shunting Inhibitory Convolutional Neural Networks, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
A Gender Recognition System Using Shunting Inhibitory Convolutional Neural Networks, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
Dr Fok Hing Chi Tivive
In this paper, we employ shunting inhibitory convolutional neural networks to develop an automatic gender recognition system. The system comprises two modules: a face detector and a gender classifier. The human faces are first detected and localized in the input image. Each detected face is then passed to the gender classifier to determine whether it is a male or female. Both the face detection and gender classification modules employ the same neural network architecture; however, the two modules are trained separately to extract different features for face detection and gender classification. Tested on two different databases, Web and BioID database, …
Automatic Recognition Of Smiling And Neutral Facial Expressions, Peiyao Li, S Phung, Abdesselam Bouzerdoum, Fok Hing Chi Tivive
Automatic Recognition Of Smiling And Neutral Facial Expressions, Peiyao Li, S Phung, Abdesselam Bouzerdoum, Fok Hing Chi Tivive
Dr Fok Hing Chi Tivive
Facial expression is one way humans convey their emotional states. Accurate recognition of facial expressions via image analysis plays a vital role in perceptual human computer interaction, robotics and online games. This paper focuses on recognising the smiling from the neutral facial expression. We propose a face alignment method to address the localisation error in existing face detection methods. In this paper, smiling and neutral facial expression are differentiated using a novel neural architecture that combines fixed and adaptive non-linear 2-D filters. The fixed filters are used to extract primitive features, whereas the adaptive filters are trained to extract more …
Automatic Classification Of Human Motions Using Doppler Radar, Jingli Li, Son Lam Phung, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
Automatic Classification Of Human Motions Using Doppler Radar, Jingli Li, Son Lam Phung, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
Dr Fok Hing Chi Tivive
This paper presents a new approach to classify human motions using a Doppler radar for applications in security and surveillance. Traditionally, the Doppler radar is an effective tool for detecting the position and velocity of a moving target, even in adverse weather conditions and from a long range. In this paper, we are interested in using the Doppler radar to recognize the micro-motions exhibited by people. In the proposed approach, a frequency modulated continuous wave radar is applied to scan the target, and the short-time Fourier transform is used to convert the radar signal into spectrogram. Then, the new two-directional, …
Automatic Human Motion Classification From Doppler Spectrograms, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Moeness G. Amin
Automatic Human Motion Classification From Doppler Spectrograms, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Moeness G. Amin
Dr Fok Hing Chi Tivive
No abstract provided.
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Dr Fok Hing Chi Tivive
We propose a new hierarchical architecture for visual pattern classification. The new architecture consists of a set of fixed, directional filters and a set of adaptive filters arranged in a cascade structure. The fixed filters are used to extract primitive features such as orientations and edges that are present in a wide range of objects, whereas the adaptive filters can be trained to find complex features that are specific to a given object. Both types of filters are based on the biological mechanism of shunting inhibition. The proposed architecture is applied to two problems: pedestrian detection and car detection. Evaluation …
Improved Facial Expression Recognition With Trainable 2-D Filters And Support Vector Machines, Peiyao Li, Son Lam Phung, Abdesselam Bouzerdoum, Fok Hing Chi Tivive
Improved Facial Expression Recognition With Trainable 2-D Filters And Support Vector Machines, Peiyao Li, Son Lam Phung, Abdesselam Bouzerdoum, Fok Hing Chi Tivive
Dr Fok Hing Chi Tivive
Facial expression is one way humans convey their emotional states. Accurate recognition of facial expressions is essential in perceptual human-computer interface, robotics and mimetic games. This paper presents a novel approach to facial expression recognition from static images that combines fixed and adaptive 2-D filters in a hierarchical structure. The fixed filters are used to extract primitive features. They are followed by the adaptive filters that are trained to extract more complex facial features. Both types of filters are non-linear and are based on the biological mechanism of shunting inhibition. The features are finally classified by a support vector machine. …
A Car Detection System Based On Hierarchical Visual Features, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
A Car Detection System Based On Hierarchical Visual Features, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
Dr Fok Hing Chi Tivive
In this paper, we address the problem of detecting and localizing cars in still images. The proposed car detection system is based on a hierarchical feature detector in which the processing units are shunting inhibitory neurons. To reduce the training time and complexity of the network, the shunting inhibitory neurons in the first layer are implemented as directional nonlinear filters, whereas the neurons in the second layer have trainable parameters. A multi-resolution processing scheme is implemented so as to detect cars of different sizes, and to reduce the number of false positives during the detection stage, an adaptive thresholding strategy …
A Shunting Inhibitory Convolutional Neural Network For Gender Classification, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
A Shunting Inhibitory Convolutional Neural Network For Gender Classification, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
Dr Fok Hing Chi Tivive
Demographic features, such as gender, are very important for human recognition and can be used to enhance social and biometric applications. In this paper, we propose to use a class of convolutional neural networks for gender classification. These networks are built upon the concepts of local receptive field processing and weight sharing, which makes them more tolerant to distortions and variations in two dimensional shapes. Tested on two separate data sets, the proposed networks achieve better classification accuracy than the conventional feedforward multilayer perceptron networks. On the Feret benchmark dataset, the proposed convolutional neural networks achieve a classification rate of …
A Human Gait Classification Method Based On Radar Doppler Spectrograms, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Moeness G. Amin
A Human Gait Classification Method Based On Radar Doppler Spectrograms, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Moeness G. Amin
Dr Fok Hing Chi Tivive
An image classification technique, which has recently been introduced for visual pattern recognition, is successfully applied for human gait classification based on radar Doppler signatures depicted in the time-frequency domain. The proposed method has three processing stages. The first two stages are designed to extract Doppler features that can effectively characterize humanmotion based on the nature of arm swings, and the third stage performs classification. Three types of arm motion are considered: free-arm swings, one-arm confined swings, and no-arm swings. The last two arm motions can be indicative of a human carrying objects or a person in stressed situations. The …
Feature Selection For Facial Expression Recognition, Abdesselam Bouzerdoum, Son Lam Phung, Fok Hing Chi Tivive, Peiyao Li
Feature Selection For Facial Expression Recognition, Abdesselam Bouzerdoum, Son Lam Phung, Fok Hing Chi Tivive, Peiyao Li
Dr Fok Hing Chi Tivive
In daily interactions, humans convey their emotions through facial expression and other means. There are several facial expressions that reflect distinctive psychological activities such as happiness, surprise or anger. Accurate recognition of these activities via facial image analysis will play a vital role in natural human-computer interfaces, robotics and mimetic games. This paper focuses on the extraction and selection of salient features for facial expression recognition. We introduce a cascade of fixed filters and trainable non-linear 2-D filters, which are based on the biological mechanism of shunting inhibition. The fixed filters are used to extract primitive features, whereas the adaptive …