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.
In this paper, we present a new approach for dynamic hand gesture recognition that uses intensity, depth, and skeleton joint data captured by Kinect sensor. This method integrates global and local information of a dynamic gesture. First, we represent the skeleton 3D trajectory in spherical coordinates. Then, we select the most relevant points in the hand trajectory with our proposed method for keyframe...
Outdoor visual surveillance systems have studied object tracking in non-overlapping multiple cameras. In this paper, we present a data association method for multi-object tracking in a non-overlapping camera network. Proposed method is based on similarity function which consists of a multi-camera topology obtained from local tracking results and matching results from person re-identification. Simulation...
In this paper, we present an open collection of simulated datasets produced using the Underwater Simulator (UWSim). These datasets contain several trajectories in simulated scenarios with various levels of turbidity. Also, several sensor to estimate the robot displacement are available. The ground truth is available by using Global Positioning System data. Those information can be used to analyse...
This paper attempts to recognize online Farsi handwriting using the freeman chain codes and hidden Markov model. Chain codes reduce the number of data with using the direction of breaks and keeping the direction of pen movement. Hence, it can be used as an effective way to recognition of online sub-words. After breaking the sub-word into component parts (main body and strokes), each part separately...
Action recognition has been one of the most popular fields of computer vision. This paper presents a novel approach to action recognition problem using the dimension reduction method, local fisher discriminant analysis, to reduce the dimension of feature descriptors as the preprocessing step after feature extraction. We propose to use sparse matrix and randomized kd-tree to modify and accelerate the...
Major commercial (AAA) games increasingly transit to a semi-persistent or persistent format in order to extend the value of the game to the player, and to add new sources of revenue beyond basic retail sales. Given this shift in the design of AAA titles, game analytics needs to address new types of problems, notably the problem of forecasting future player behavior. This is because player retention...
Recent advances in image captioning task have led to increasing interests in video captioning task. However, most works on video captioning are focused on generating single input of aggregated features, which hardly deviates from image captioning process and does not fully take advantage of dynamic contents present in videos. We attempt to generate video captions that convey richer contents by temporally...
Person re-identification is the process of recognizing a person across a network of cameras with non-overlapping fields of view. In this paper we present an unsupervised multi-shot approach based on a patch-based dynamic appearance model. We use deformable graph matching for person re-identification using histograms of color and texture as features of nodes. Each graph model spans multiple images...
In this paper, a robust moving camera calibration method is proposed in order to synthesize a free viewpoint soccer video with a high degree of accuracy. The main problem in video registration-based moving camera calibration is that the calibration accuracy is very low if the detected feature points are from moving objects. In order to solve this problem, the proposed method tracks the feature points...
Video co-segmentation typically refers to the task to jointly segment common objects existing in a given group of videos. In practice, high-dimensional data such as videos are often conceptually thought of being drawn from a union of subspaces corresponding to multiple categories. Therefore, segmenting data into respective subspaces, known as subspace clustering, has widespread applications in computer...
Action recognition has been one of the challenging problems in the computer vision community. Most of the recent research work in this area exploits the motion features captured by dense trajectory descriptors. On the other hand, static image classification has seen the rise of deep learning architectures, with evidence that the output of intermediate layers could be successfully employed as a low...
Mass gatherings to protest or demonstrate can sometimes turn violent and take the shape of a riot. It has been observed that generally demonstrations deteriorate to riots after instigation by perpetrators. Therefore, identification of instigator(s) can prevent people from turning into a mob and help law enforcement agencies to keep them under control. To the best of our knowledge there has been no...
This work proposes a trajectory clustering-based approach for segmenting flow patterns in high density crowd videos. The goal is to produce a pixel-wise segmentation of a video sequence (static camera), where each segment corresponds to a different motion pattern. Unlike previous studies that use only motion vectors, we extract full trajectories so as to capture the complete temporal evolution of...
In contrast to still image analysis, motion information offers a powerful means to analyze video. In particular, motion trajectories determined from keypoints have become very popular in recent years for a variety of video analysis tasks, including search, retrieval and classification. Additionally, cloud-based analysis of media content has been gaining momentum, so efficient communication of salient...
Ferroresonance is complicated phenomenon for its various modes. In this paper, two nonlinear features are extracted based on nonlinear analytical Technique. The features can be used to analyze the motion characteristics of the ferroresonance system of the overvoltage time series. The study on overvoltage acquired from a power substation shows that the feature is very useful for ferroresonance mode...
Chronic pain is a disease that the patients suffers a lot in their daily life and it is difficult to be released completely. It is difficult to manage because pain can come anytime and it is unpredictable. However, the pain can be represented by the pain related behaviors such as guiding and abrupt actions. In this paper, we will develop a machine learning based system that can detect the pain related...
Despite the huge research on crowd on behavior understanding in visual surveillance community, lack of publicly available realistic datasets for evaluating crowd behavioral interaction led not to have a fair common test bed for researchers to compare the strength of their methods in the real scenarios. This work presents a novel crowd dataset contains around 45,000 video clips which annotated by one...
Distraction during driving is a growing concern for global road safety. Different activities impertinent to driving hinder the concentration of driver on road and often cause substantial damage to life and property. For making driving safe, an algorithm is proposed in this paper that is capable of detecting distraction during driving. The proposed algorithm tracks key body parts of the driver in video...
The characteristics like density of objects, their contrast with respect to surrounding background, their occlusion level and many more describe the context of the scene. The variation of the context represents ambiguous task to be solved by tracker. In this paper we present a new long term tracking framework boosted by context around each tracklet. The framework works by first learning the database...
In this paper, we focus on the important topic of violence recognition and detection in surveillance videos. Our goal is to determine if a violence occurs in a video (recognition) and when it happens (detection). Firstly, we propose an extension of the Improved Fisher Vectors (IFV) for videos, which allows to represent a video using both local features and their spatio-temporal positions. Then, we...
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.