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How much does it hurt? Accurate assessment of pain is very important for selecting the right treatment, however current methods are not sufficiently valid and reliable in many cases. Automatic pain monitoring may help by providing an objective and continuous assessment. In this paper we propose an automatic pain recognition system combining information from video and biomedical signals, namely facial...
One of the first steps in most facial expression and facial analysis systems is the localization of prominent facial feature points. In this paper we present a novel approach for facial feature point detection using Simplified Gabor Wavelets (SGW). The classifier is built in cascades, where each stage of the cascade is a Gentle-AdaBoost trained classifier. In addition, we suggest a confidence based...
This paper proposes a system to recognize isolated American Sign Language and numbers in real-time from Bumblebee stereo camera using Latent-Dynamic Conditional Random Fields (LDCRFs). Our system is based on three main stages: preprocessing, feature extraction and classification. In preprocessing stage, color and 3D depth map are used to detect and track the hand. The second stage, combining features...
The governing behaviors of individuals in crowded places offer unique and difficult challenges, and limit the scope of conventional surveillance systems. In this paper, we investigate the crowd behaviors and localize the anomalies due to individual's abrupt dissipation. The novelty of the proposed approach can be described in three aspects. First, we introduce block-clips by sectioning the video segments...
Facial Feature point detection, and object detection in general, is not only a problem of accuracy but also a problem of computation time. Integral images provide fast computation time. Several classes of features working on these integral images have been introduced. So far in most cases only integral images of 0° and 45° have been used. We will present our first results of exploring the performance...
This paper proposes a forward spotting method that handles hand gesture segmentation and recognition simultaneously without time delay. To spot meaningful gestures of numbers (0-9) accurately, a stochastic method for designing a non-gesture model using Conditional Random Fields (CRFs) is proposed without training data. The non-gesture model provides a confidence measures that are used as an adaptive...
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