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We present the results of analyzing gait motion in first-person video taken from a commercially available wearable camera embedded in a pair of glasses. The video is analyzed with three different computer vision methods to extract motion vectors from different gait sequences from four individuals for comparison against a manually annotated ground truth dataset. Using a combination of signal processing...
With the development of information technology, the automatic recognition of human action from video becomes a very popular research topic. In this paper, we review recent state-of-the-art of human action recognition methods in videos. First, we compare several notable handcrafted methods. Then we introduce some deep learning action recognition models. As deep learning becomes hot spot of research...
Computer Vision is gaining importance with wide applications in video surveillance, video retrieval and analysis, and human — computer interaction. Detection and recognition of human action from the video databases is really a difficult and challenging task. In this paper, video based human action detection and recognition is addressed and performed on KTH dataset and on real-time videos. At first,...
This paper presents a method for detecting unusual human activity from a video stream, depending on whether a sequence of human actions differs from the usually observed sequences of human actions. The proposed method extracts low-level features from a video stream during a short time period for describing human actions, and the extracted sequence of the low-level features is used for describing human...
An improved moving object segmentation approach which extracted motion field from H.264 compressed domain is proposed. Pre-treatments such as vector median filtering and forward block vector accumulation are used to obtain more obvious motion field. Then mix and hierarchical clustering algorithm based on improved k-means and EM is exploited to segment the moving on the macro-block level and on the...
The camera of traffic system takes numerous photos every day. It's critically important for judging kinds of car movements and intelligent transportation to pick up the outlines of automobiles and fix their positions. However, the popular car positioning algorithm is unable to reach the required fast speed in this field. In this paper we will provide readers with an algorithm to locate cars based...
Aim of this work is to propose a robust solution to the correspondence problem in multi-camera systems applied to video surveillance. The proposed system merges two different approaches: Self Organizing Map (SOM) and feature based corresponding analysis. The novelty of this work consists of the used approach and the ability to work without the assumption of epipolar geometry. The proposed approach...
Human activity recognition has become very popular in the field of computer vision. In this paper, we present a simple, robust and computationally efficient algorithm, architecture and implementation to recognise and classify human activities in real-time using very few training data. We employ a spatio-temporal representation of human activities by combining trajectory information and invariant spatial...
Surveillance videos are often compressed for transmission or storage. It is desirable to be able to perform automatic event detection in the compressed domain directly. In this paper, we investigate the use of motion trajectories for video activity detection in the compressed domain. We show that it is possible to extract reliable motion trajectories directly from compressed H.264 video streams. To...
Detection of shot transitions servers as the preliminary step to video indexing and retrieval. Locally linear embedding (LLE) algorithm fails when it is applied to video with multi-shot. In this paper, we present a novel framework of shot transitions detection. The method involves two processes: First we extract the manifold feature of shot transition using LLE through addition of virtual frames on...
Smoke detection in video surveillance images has been studied for years. However, given an image in open or large spaces with typical smoke and the disturbance of commonly moving objects such as pedestrians or vehicles, robust and efficient smoke detection is still a challenging problem. In this paper, we present a novel and reliable framework for automatic smoke detection. It exploits three features:...
This paper proposes a method to detect speed variation of a moving human target, based on polar projection feature. Through even-grid-polar mapping, two polar projection feature images, namely r-projection and q-projection, are obtained respectively. It is found that the frequency of double-peak in q-projection feature image series in a motion cycle is sensitive to speed variation and can be utilized...
This paper presents a new algorithm for detecting the human's reciprocating motion in pornographic videos. First, the motion vector is extracted from mpeg video stream and pretreated so that the motion features are extracted by analyzing the motion rule of the objectionable videos. Then the whole videos are detected through setting a threshold. Experimental results demonstrate that the correct recognition...
In this paper, an automated video surveillance for crime scene detection using statistical characteristics is presented. The system is named Public Safety System(PSS). If the scene shows some peculiar situation such as purse-snatching, kid napping and fighting on the street, the PSS recognize the situation and automatically report to agency. Localization of moving targets in the scene and human behavior...
In this paper, we propose two video fingerprinting methods that are robust to both geometric and non-geometric modifications on content. Both of the proposed methods are based on computation of moment invariants as features from concentric circular regions. The two methods differ in the way they capture appearance and motion information from video. In one method, we capture motion information by computing...
The moving objects are what attract most attention in the video surveillance system, and also the key part for study. Currently, the video surveillance system relies much on the subjective initiative of the observers while having the real-time surveillance. In this study, applying the mixture Gaussian model algorithm, the profile image of the moving objects in the picture got from the video surveillance...
Intelligent video monitoring is a new technology originally developed on the basis of video image processing technology. Aiming at the defects of monitoring conducted by man in the conventional practice, the automatic alarming technology based on intelligent video monitoring was studied. Frame difference-based dynamic background refreshing algorithm was applied to monitored scenes to carry out cutting...
We propose a method of shot boundary detection based on the co-occurrence of global motion in video stream. In addition to the conventional features based on appearance and local motion, we apply ST (Space-Time) patch analysis for detecting global motion in video stream. And then we perform shot boundary detection by constructing AdaBoost classifiers which represent the co-occurrence of global motion...
Intelligent surveillance systems have become an important research issue recently. They can provide an early warning or help us to retrieve interested video frames. The motion detection techniques play an important role in these two applications. In this paper, we propose an effective surveillance video retrieval method based upon the motion detection technology. We can use this method to search frames...
Due to a high demand for efficient video summarisation and video adaptation technologies, this paper focuses on utilisation of compressed domain feature extraction and hierarchical analysis of motion information in scalable video in order to generate intuitive visual summaries. By combining the analysis of inherently hierarchical motion activity measure and a fast geometrical curve simplification...
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