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This paper begins with a discussion of the deficiency of current algorithms which use the number of the changing points of frame-difference as the threshold to determine a moving object. Based on human morphology, the feature of the human body in video surveillance is analyzed. Secondly, "the head and shoulder projection curve"," the proportion of head hair "and "height-width...
Human gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present...
Human action classification is an important task in computer vision. The Bag-of-Words model uses spatio-temporal features assigned to visual words of a vocabulary and some classification algorithm to attain this goal. In this work we have studied the effect of reducing the vocabulary size using a video word ranking method. We have applied this method to the KTH dataset to obtain a vocabulary with...
The paper presents a high speed video processing algorithm designed to measure several parameters related to eyelid movements during blinking. First, the facial features of the subject are detected and tracked; then, the eye regions of interest are extracted using data regarding face orientation and eyebrows position. In the next stage, eye contour and representative lines for upper and lower eyelids...
The question of scene information whether can help realistic action recognition has been investigated in this paper. The salience region of each frame in video was acquired by using Itti-Koch algorithm. The information outside the salience region represented scene information. Two action recognition methods were tested on the YouTube action dataset. One method got rid of partial scene information,...
Human visual system can detect salient region fast and reliably, however, it is a big challenge to build a corresponding visual computing model. In this paper, a model of salient region detection based on local and regional features is presented. Firstly, the image is divided into 8 × 8 sub-blocks. Secondly, the local feature and regional feature of each sub-block are calculated. Local feature which...
In order to solve the problem that Omni-directional faces, which was in images with complex context, couldn't be detected, an eye-core based face detection model was proposed. In the proposed model, the technique of HSI based skin detection combined with eye-core detection was used to detect eyes, and then image rotation, features extraction from images and neural network based classification were...
Visual attention is useful for computer vision and it has been applied in image compression and object recognition. In existing methods on saliency detection, most of them are unrelated to the depth feature. So we propose a bottom-up saliency detection model that combines the depth feature with region contrast based saliency model and the precision and recall rate of our algorithm is higher than those...
In this paper, a new statistical-based ECG algorithm, which applies the idea of matching Reduced Binary Pattern, is proposed to seek a timely and accurate human identity recognition. A comparison with previous researches, the proposed design requires neither waveform complex information nor de-noising pre-processing in advance. Our algorithm is tested on the public MIT-BIH arrhythmia and normal sinus...
Pedestrian detection is of much importance for its practical applications. This paper develops a novel pedestrian detection system which consists of three stages: motion region detection based on background modeling, feature extraction in the guidance of prior information, and map-based classification applying support vector machine (SVM) and Adaboost. First of all, an adaptive Gaussian Mixture Model...
We present an automated approach to music search and playlist generation based on fractal dimensions of music. We compute 372 power-law metrics per song capturing statistical proportions of musical material. Using attribute selection and principal component analysis, we have reduced these metrics to approximately 45 independent features. These have been shown to capture important aspects of music...
Local spatiotemporal detectors and descriptors have recently become very popular for video analysis in many applications. They do not require any preprocessing steps and are invariant to spatial and temporal scales. Despite their computational simplicity, they have not been evaluated and tested for video analysis of facial data. This paper considers two space-time detectors and four descriptors and...
In this paper, we apply Web images to the problem of automatically extracting video shots corresponding to specific actions from Web videos. Our framework modifies the unsupervised method on automatic collecting of Web video shots corresponding to the given actions which we proposed last year [9]. For each action, following that work, we first exploit tag relevance to gather 200 most relevant videos...
To detect human sex from complex background, illumination variations and objects by machine is very difficult but important for adaptive information service. In this research, we present a preliminary design and experimental results of gender recognition from walking movements that utilizes gait energy image(GEI) with denoised energy image(DEI) pre-processing as support vector machine(SVM) classifier...
Falls are a major threat to the independence and quality of life of elderly people. As the worldwide population of elderly increases each year, responding to falls is essential. Computer vision systems provide a new promising solution in responding falls through detecting fall events. This paper presents a new technique in detecting falls based on human shape variation. The proposed visual based fall...
Video saliency mechanism is crucial in the human visual system and helpful to object detection and recognition. In this paper we propose a novel video saliency model that video saliency should be both consistently salient among consecutive frames and temporally novel due to motion or appearance changes. Based on the model, temporal coherence, in addition to spatial saliency, is fully considered by...
In this paper, we present a novel approach for human action recognition with histograms of 3D joint locations (HOJ3D) as a compact representation of postures. We extract the 3D skeletal joint locations from Kinect depth maps using Shotton et al.'s method [6]. The HOJ3D computed from the action depth sequences are reprojected using LDA and then clustered into k posture visual words, which represent...
We describe a novel learning scheme for hidden dependencies in video streams. The proposed scheme aims to transform a given sequential stream into a dependency structure of particle populations. Each particle population summarizes an associated segment. The novel point of the proposed scheme is that both of dependency learning and segment summarization are performed in an unsupervised online manner...
Our primary motivation in this paper is to determine whether evolved texture feature extraction programs are competitive with human derived programs for a difficult real world texture classification problem. The problem involves distinguishing images of three classes of bulk malt. There are subtle differences between the three classes. We have used a number of human derived methods, Haralick, Gabor,...
In the past decade, the bag-of-feature model has established itself as the state-of-the-art method in various visual classification tasks. Despite its simplicity and high performance, it normally works as a black box and the classification rule is not transparent to users. However, to better understand the classification process, it is favorable to look into the black box to see how an image is recognized...
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