Rami Alazrai

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This paper presents a hierarchal, two-layer, connectionist-based human-action recognition system (CHARS) as a first step towards developing socially intelligent robots. The first layer is a K-nearest neighbor (K-NN) classifier that categorizes human actions into two classes based on the existence of locomotion, and the second layer consists of two(More)
This paper presents a real-time emotion recognition system (RTERS) as a first step towards developing a socially intelligent robot. The RTERS first localizes faces in a sequence of images, then features are extracted and passed to a recognition engine that codes facial expressions into one of seven different emotional states: happiness, sadness, fear,(More)
This paper presents a Nonlinear AutoRegressive with eXogenous input (NARX)-based approach for human-emotion recognition from an input video. The dynamics of facial expressions are first captured by performing a temporal-spatial analysis by extracting local and spatial features using a pyramid of histograms of oriented gradients (PHOG) descriptor. Then the(More)
Late development and evolution of high degree-of-freedom (DOF) robotic hands have seen great technological strides to enhance the quality of life for amputated people. A robust hand kinematic estimation mechanisms have shown promising results to control robotic hands that can mimic the human hand functions and perform daily life hand dexterous tasks. In(More)
Ultrasound imaging is commonly used for breast cancer diagnosis, but accurate interpretation of breast ultrasound (BUS) images is often challenging and operator-dependent. Computer-aided diagnosis (CAD) systems can be employed to provide the radiologists with a second opinion to improve the diagnosis accuracy. In this study, a new CAD system is developed to(More)
With the aging of society population, efficient tracking of elderly activities of daily living (ADLs) has gained interest. Advancements of assisting computing and sensor technologies have made it possible to support elderly people to perform real-time acquisition and monitoring for emergency and medical care. In an earlier study, we proposed an(More)
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