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.
This study proposes a technique to generate effective features to classify fundamental human body postures in image sequences such as standing, sitting on the chair, sitting on the floor, bending, and lying down. Truncated discrete cosine transform (DCT) is utilized to obtain features before performing truncated singular value decomposition (SVD). It has been shown that the truncated DCT disregards...
In this paper, a novel feature for activity recognition from vertical top-view depth image sequences is firstly proposed. Most of previous works are focusing mainly on the side-view depth or color image sequences, which unfortunately may encounter occlusion problems. Therefore, top-view camera setting is adopted in our research. Based on the idea of computed tomography (CT) from medical imaging, the...
This paper proposes a simple spatial feature combined with temporal characteristics to classify human interactions from surveillance cameras, which are far from the action scene. For the first stage, data is collected from a horizontal view. Then, the history of distance between two persons is stored during time as a temporal feature called distance signature. We use Spatio-Temporal Interest Points...
A method to distinguish different human motions including walking, running, and wandering in the surveillance video is proposed in this paper. First of all, a block-based background extraction method is used to construct the background image. Second, the moving object can be detected by the use of RGB-based motion detection method and then the shadow removal scheme. Finally, a temporal signal representing...
Pedestrian detection is one of the most important techniques for surveillance applications. This paper proposes an effective method for pedestrian detection in low-contrast images. The main characteristic of the proposed method is a two-stage moving object extraction. In the first stage, the watershed algorithm is used to extract multiple regions of moving objects. In the second stage, a novel criterion...
This paper is concerned with investigating, experiencing, and validating some non classic techniques for compound moving objects analysis in successive video frames. This composite-tasks problem has so far been very`rarely' dealt with as a `single' multidirectional problem, it has always been handled as several separate unidirectional, or seldom bidirectional problems. The paper exhibits an HCI system...
Automatic traffic abnormality detection through visual surveillance is one of the critical requirements for Intelligent Transportation Systems (ITS). In this paper, we present a novel algorithm to detect abnormal traffic events in crowded scenes. Our algorithm can be deployed with few setup steps to automatically monitor traffic status. Different from other approaches, we don't need to define region...
In this paper, we address the task of appearance based person reidentification in infrared image sequences. While common approaches for appearance based person reidentification in the visible spectrum acquire color histograms of a person, this technique is not applicable in infrared for obvious reasons. To tackle the more difficult problem of person reidentification in infrared, we introduce an approach...
This paper is concerned with investigating, experiencing, and validating a local adaptive threshold system with compound motion analysis. The motivation here is to analyze moving objects in outdoor/indoor video frames with respect to: movement detection, objects segmentation, features extraction besides DFT-based velocity computation. The underlying methodology exhibits a single correlation of the...
This paper presents a new behavior classification system that can analyze human behaviors from arbitrary views. Technically, if different viewing angle are used for observing a person, his appearances will change significantly. To freely recognize his behaviors, traditional methods tend to adopt 3-D data for behavior analysis. However, its inherent correspondence process will make it inappropriate...
In recent years, the research on detecting human faces in color image and in video sequence has been attracted with more and more people, but automatic human face detection from images in surveillance and biométrie applications is still a challenging task due to the computation inaccuracies and the continuous nature of some transformations. In this paper we propose a novel face detection algorithms...
Automatic detection of an unusual event in video sequence has an interesting application in security surveillance. This paper proposed a method to detect a gathering event without tracking individuals by using background subtracted blobs as the event feature and dividing the video frame into blocks. The feature sequences are encoded with hidden Markov model to detect the gathering event. The experimental...
This paper presents an approach to count the number of people that enters or leaves metro trains. This is a challenging scenario where usually people crowd around the train doors, and therefore it is not possible a direct approach that segments and counts individuals. The proposed technique is based on a statistical analysis of the flow obtained from the motion vectors at corner points. The method...
We here present a multi-sensor data fusion architecture that takes into account the performance of video sensors in detecting moving targets for video surveillance purposes. Target detection and tracking is performed via classification by an ensemble of classifiers learned online using heterogeneous features for each target. A novel approach is then used to estimate the position of the target on the...
Unmanned aerial vehicles (UAVs) are regularly outfitted with payloads that include high resolution surveillance cameras. These surveillance systems have provided the military with the opportunity to monitor battlefields and remote terrain, carryout reconnaissance missions and track targets all from distant ground stations without endangering UAV operators. As with any remote sensing technology there...
This paper presents an automatic traffic surveillance system which is utilized to monitor the traffic intersections. Moving vehicles are extracted accurately from video sequences based on improved background modeling and object tracking method. In this paper, 16 types of general traffic behaviors at intersections are specifically defined and the traffic information collected from the tracking results...
Event detection and recognition is an active and challenging topic recent in computer vision. The technique could be applied in many visual surveillance systems. This paper describes a new method of recognizing events from video sequences in an office environment. The proposed approach is the vision based human motion analysis via motion history image (MHI) sequences and is invariant to body shape,...
In this paper a view-independent head tracking system applying an Active Shape Model based particle filter is used to find precise image sections. DCTmod2 feature sequences are extracted from these sections and given as input to Cyclic Pseudo two-dimensional Hidden Markov Model based classifiers. These classifiers are trained to recognize the identity of the shown persons. The video material is recorded...
A novel color correlogram based particle filter was proposed for an object tracking in visual surveillance. By using the color correlogram as object feature, spatial information is incorporated into object representation, which yields a reliable likelihood description of the observation and prediction for tracking the objects accurately. The capability of the tracker to tolerate appearance changes...
The capability of extracting moving objects from a video sequence captured using a static camera is a typical first step in visual surveillance. This procedure is called a background subtraction (BGS), and it uses the temporal distribution of pixel values over the sequence of frames. Pixel based BGS can be improved by considering the spatial coherence around each pixel, and in this paper we present...
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.