Learn More
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)
Falls are a common cause of injuries and traumas for elderly and could be life threatening. Delivering a prompt medical support after a fall is essential to prevent lasting injuries. Therefore, effective fall detection could provide urgent support and dramatically reduce the risk of such mishaps. In this paper, we propose a hierarchical classification(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)
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)
This paper presents a new approach for fall detection from partially-observed depth-map video sequences. The proposed approach utilizes the 3D skeletal joint positions obtained from the Microsoft Kinect sensor to build a view-invariant descriptor for human activity representation, called the motion-pose geometric descriptor (MPGD). Furthermore, we have(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)