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In this paper, a novel method based on Phase Spectrum of Quaternion Fourier Transform (PQFT) for anomaly detection in crowd is presented. The proposed method mainly consists of two parts: quaternion feature representation and construct of abnormal saliency map. In the first stage, motion and appearance information are both considered and a quaternion feature representation is proposed for temporal...
Human Computer Interaction would be much more smooth with the implementation of rapid recognition, the aim of which is to recognize the hand gesture before it is completed. In this paper, a rapid recognition for dynamic hand gestures using leap motion is proposed. The database contains the three-dimensional motion trajectory of the numbers and the alphabet (36 gestures in total) which captured by...
This paper introduces a novel approach to predict human motion for the Non-binding Lower Extremity Exoskeleton (NBLEX). Most of the exoskeletons must be attached to the pilot, which exists potential security problems. In order to solve these problems, the NBLEX is studied and designed to free pilots from the exoskeletons. Rather than applying Electromyography (EMG) and Ground Reaction Force (GFR)...
There are many shape-similar gestures which cause errors in the process of hand gesture recognition. In this paper, a new method which can distinguish the similar gestures was proposed. The information of motion trajectory is captured by a leap motion in three-dimension space, and the orientation characteristics are quantified and coded as the feature. Then the Hidden Markov Model (HMM) algorithm...
Most existing methods for abnormal event detection in the literature are relied on a training phase. Different from conventional approaches for abnormal event detection, a saliency attention based abnormal event detection approach is proposed in this paper. It is inspired by the visual attention mechanism that abnormal events are those which attract attention mostly in videos. The temporal and spatial...
Real-time performance can be greatly improved, if the early recognition is implemented. In this paper, a dynamic hand gesture early recognition system is proposed. The system can recognize the gesture before it is completed. Our method is based on the Hidden Semi-Markov Models. Three-dimensional information of the gesture trajectory collected by leapmotion is the main data we used. Experiments on...
In this paper, we propose a method based on the SVM algorithm to recognize dynamic hand gestures. The information of motion trajectory is captured by a leap motion in three-dimension space. A new methodology of feature extracting is proposed to guarantee the length of samples being the same. The elements of feature vectors are ranged according to two different criteria: one is the amplitude of the...
Abnormal behavior detection has recently gained growing interest from computer vision researchers. In this paper, the gait-analysis-based abnormal detection is proposed for walking scenes, where gaits of people are analyzed in all kinds of situations and the gait data are utilized to construct the basic gait model. Walking people in the crowd are tracked and their activities silhouettes are abstracted...
The aging of population has become a social problem and fall is a major health risk in the elderly. To this end, this paper presents a novel approach for fall detection applied to an intelligent household surveillance robot. Silhouette based features are extracted, including aspect ratio of minimal bounding box of the human silhouette, approximated elliptical eccentricity, normalized central moments...
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