The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A novel model of fuzzy clustering neural network is discussed, which synthesizes unsupervised fuzzy competitive learning algorithm and self-organized competitive network. Based on this model, an algorithm of abrupt video shot boundary detection is presented which is a two-stage clustering on a linear feature space. The experimental results obtained demonstrate that the algorithm is feasible and efficient.
Wireless Capsule endoscopy (WCE) has been developed to allow direct view of the entire small bowel in human body in a noninvasive manner for the first time. But the visual inspection of a large number of video frames produced in each examination poses a tedious task to physicians. In this paper, we propose a novel scheme aiming for reduction of the number of frames in a video so as to partially solve...
Facial Expression Recognition (FER) from video is an essential research area in the field of Human Computer Interfaces (HCI). In this work, we present a new method to recognize several facial expressions from time sequential facial expression images. Firstly the video sequence is converted to image frames. Sequentially each image frame is subjected to image pre processing. Then the features are extracted...
A hybrid particle swarm optimization (PSO)-based wavelet neural network (WNN) for Video OCR is presented in this paper. Video OCR is an important task towards enabling automatic content-based retrieval of digital video databases. However, since text is often displayed against a complex background, its detection and extraction is a challenging problem. In this paper, wavelet transformation is done...
This paper addresses the problem of vowels recognition in patients after total laryngectomy using combined visual and acoustic features. The linear prediction coefficients were estimated from speech signal using weighted recursive least squares algorithm. Ten cross-sectional areas of vocal tract model were calculated. Face expression parameters related to the spoken vowel were extracted from video...
This paper discusses the problem of object area detection of video frames. The goal is to design a pixel accurate detector for grass, which could be used for object adaptive video enhancement. A boosting neural network is used for creating such a detector. The resulted detector uses both textural features and color features of the frames.
In this paper we study the problem of Chinese character recognition in video. We propose a series of algorithms on Chinese character division, tracking. Based on them we design a multi-level sorter. Firstly we extract the features of some samples and employ K-means clustering algorithm to carry on I level classification. Secondly, we employ the algorithm of multi back propagation neural network (MBPNN)...
Locally linear embedding (LLE) is an elegant nonlinear method for feature extraction and manifold learning, which attempt to project the original data into a lower dimensional feature space by preserving the local neighborhood structure. However, LLE algorithm fails when it is directly applied to video with multi-shot. In this paper, video manifold feature is defined firstly, and then using LLE we...
Detecting human activities automatically in a video stream in various scenes is a challenging task. The major difficulty of this task lies in how to extract the spatial and temporal features of video sequences so that the human activities can be recognized. To tackle this problem, we propose a new classifier model using a BCM-based spiking neural network, where the auto-regulated plasticity and meta-plasticity...
A novel two dimensional complex wavelet transform (2D-CWT) for video-based face feature extraction is proposed As 2D-CWT has its merit as follows: insensitive to image pixel shift, directional selecri??vity, and computation efficiency in the dual-tree structure, it turns out to be useful for face feature extraction in the video clips. In the proposed system, 2D-CWT features are extracted from the...
How to integrate exercises and entertainments by applying computer technology to make exercises more entertaining, or to make entertainments more fascinating, has become a popular topic in the world. It aims to realize the human-computer interaction by using the technical features of integrating games and exercises. Face-recognition as a key technique in face information processing starts to draw...
Video artificial text detection is a challenging problem of pattern recognition. Current methods which are usually based on edge, texture, connected domain, feature or learning are always limited by size, location, language of artificial text in video. To solve the problems mentioned above, this paper applied SOM (Self-Organizing Map) based on supervised learning to video artificial text detection...
A novel method of crowd estimation is proposed in this paper: Firstly, surveillance image is divided into bit planes by OSTU algorithm, the pixel ratio of foreground to background and complexity of bit planes are taken as feature vectors of crowd estimation. The degree of crowd density of the scene is classified into several grades, BP neural network is used for training and then the classification...
This paper proposes a localization method of Uygur words in video. First, the video color frame image is preprocessed, while the wavelet transformation is applied and texture entropy is calculated using three-stage wavelet in high frequency details. The entropy is regarded as an important parameter to extract texture characteristic of the image. Further segment each image into some sub-domains and...
Neural network analysis, an important branch in data mining, has been widely used in statistical analysis, pattern recognition, image processing, biological species division and customer division. Based on division method, the paper rationally selected initial class center, dynamically regulated the number of classification during image classification, and proposed an image recognition method. In...
The paper describes combined approach to face detection for grayscale images using the combined cascade of neural network classifiers which consists of Haar-like features' cascade of weak classifiers and convolutional neural network. The combined cascade with proposed face candidates' verification method allows achieving one of the best detection rates on CMU test set and a high processing speed suitable...
The technique of performing classification using association rule mining (ARM) has been adopted to bridge the multimedia semantic gap between low-level features and high-level concepts of interest, taking advantages of both classification and association rule mining. One of the most important research approaches in ARM is to investigate the interesting-ness measure which plays a key role in association...
Detecting vehicles from video sequence is very challenging due to the wide varieties of vehicle appearances and the complexity of the backgrounds. At present, many algorithms in the image recognition have a narrow applicability and a weak real-time. Aiming at this problem, a recognition method which was combined by features extraction using Gabor wavelet and BP neural network algorithm for the classification...
An improved, intelligent pedestrian counting system, using images obtained from a single video camera, is described in this paper. This system is capable of detecting and counting a group of pedestrians in the region of interest. Groups can be extracted by using the image processing method, and a kernel-induced probabilistic neural network (KPNN) employed to perform the classification, and estimate...
The objective of this study is to investigate alternative ways for representing suitably, with the fewest possible assumptions, the information derived from video recordings. It proposes a set of statistical descriptors capable of summarizing all the available information from each video frame. A sequence of such features expresses the object motion implicitly without the need for object detection...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.