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Visual Surveillance in dynamic scenes is one of the most active research areas. In this paper an algorithm has been proposed to detect human behaviours for visual surveillance. This method gives an efficient face recognition technique in dynamic scenario using Principal Component Analysis and Minimum distance classifier.
Effects of driver's states adaptive driving support systems is highly expected for the prevention of traffic accidents. In order to create this constituent technology, detecting driver's psychosomatic states which occurs just before a traffic accident is essential. Therefore driver's distraction is thought as one of important factors. This study focused on detecting driver's cognitive distraction,...
Facial expressions are the facial changes in response to a person's internal emotional states, intentions or social communications. In this paper, we fulfill the recognition of facial action units, i.e., the subtle change of facial expressions, and emotion-specified expressions. Our automatic facial expression analysis system includes face detection, facial component extraction, tracking and representation,...
This paper outlines several multimedia systems that utilize a multimodal approach. These systems include audiovisual based emotion recognition, image and video retrieval, and face and head tracking. Data collected from diverse sources/sensors are employed to improve the accuracy of correctly detecting, classifying, identifying, and tracking of a desired object or target. It is shown that the integration...
We investigate the problem of automatically labelling faces of characters in TV or movie material with their names, using only weak supervision from automatically-aligned subtitle and script text. Our previous work (Everingham et al. [8]) demonstrated promising results on the task, but the coverage of the method (proportion of video labelled) and generalization was limited by a restriction to frontal...
Probabilistic and statistical model analysis methods based on the Bayesian approach have recently been applied to face tracking. Here, we propose a face tracking method based on a Bayesian framework of image sequences. We assume that an observed space is three-dimensional (3D) and model facial shape, rotation and translation in 3D. A 3D positional hypothesis is generated using the facial translation...
Interactive mobile robots require object/subject detection in very visually complex environments. In the field of computer vision, specially when applied to robotics, several approaches like face detection, face recognition and pedestrian detection often have to deal with issues associated to bad illumination and strong featured background. These issues imply lack of performance because human detection...
Robotic assistants designed to coexist and communicate with humans in the real world should be able to interact with them in an intuitive way. This requires that the robots are able to recognize typical gestures performed by humans such as head shaking/nodding, hand waving, or pointing. In this paper, we present a system that is able to spot and recognize complex, parameterized gestures from monocular...
Expressions carry vital information in sign language. In this study, we have implemented a multi-resolution active shape model (MR-ASM) tracker, which tracks 116 facial landmarks on videos. Since the expressions involve significant amount of head rotation, we employ multiple ASM models to deal with different poses. The tracked landmark points are used to extract motion features which are used by a...
This paper proposes a novel spontaneous facial expression classification method using the facial motion magnification which transforms the subtle facial expressions into the corresponding exaggerated facial expressions. Facial motion magnification consists of four steps: First, we perform the active appearance model (AAM) fitting to extract 70 facial feature points in the face image sequence. Second,...
In spatial face detection stage, in order to eliminate the influence of luminance, a two-dimension Gaussian distribution function, based on the chrominance plane of YCbCr color space, is constructed, then the moving skin area is determined by the luminance component Y, the moving face is detected by support vector machine classifier. In face temporal tracking stage, the eigeface similarity measurement...
In this work we develop a fast facial expression recognition system with low complexity by proposing a method that does not need face detection for facial characteristics tracking. Moreover, our simple feature selection differentiates between the expressions and accelerates the systempsilas performance. In this system, selected facial feature points from the first frame to the last are tracked automatically...
This paper presents a very simple feature-based nose detector in combined range and amplitude data obtained by a 3D time-of-flight camera. The robust localization of image attributes, such as the nose, can be used for accurate object tracking. We use geometric features that are related to the intrinsic dimensionality of surfaces. To find a nose in the image, the features are computed per pixel; pixels...
This paper deals with the fully automatic extraction of classifiable person features out of a video stream with challenging background. Basically the task can be split in two parts: Tracking the object and extracting distinctive features. In order to track a person, a system composed of an active shape model embedded in a particle filter framework has been built. The output-a shape representing the...
Since skin-tone is luminance dependent, it's sensitively affected by illumination variation. Thus, the stability and accuracy of skin-based face tracker would be degraded dramatically while environment changed; especially platform of the system is notebook or portable device. In this study we propose an effective illumination recognition technique, utilizing k-nearest neighbor classifier combined...
Facial expression recognition is necessary for designing any realistic human-machine interfaces. Previous published facial expression recognition systems achieve good recognition rates, but most of them perform well only when the user faces the camera and does not change his 3D head pose. We propose a new method for robust, view-independent recognition of facial expressions that does not make this...
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