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.
Multi-object model-free tracking is challenging because the tracker is not aware of the objects' type (not allowed to use object detectors), and needs to distinguish one object from background as well as other similar objects. Most existing methods keep updating their appearance model individually for each target, and their performance is hampered by sudden appearance change and/or occlusion. We propose...
Computer Vision and Machine Learning are the key to develop autonomous robots. While engaged with a IEEE Open Challenge, in which the robots need to recognize a miniature of a cow, we saw a solution in these areas. The main contribution of this paper is the algorithm implemented to identify and follow a known object, the miniature of a cow. We are constructing an application based on Image Processing...
We present an end-to-end system for detecting and clustering faces by identity in full-length movies. Unlike works that start with a predefined set of detected faces, we consider the end-to-end problem of detection and clustering together. We make three separate contributions. First, we combine a state-of-the-art face detector with a generic tracker to extract high quality face tracklets. We then...
Object Tracking is an important task in Computer Vision, which has gained increasing attention from academia to industry. In this paper, we propose a real-time tracking system based on weak segmentation. Different from general tracking by detection systems, we do not classify objects into car, cat or bike, instead we just classify the image into object area and non-object area. Many tracking systems...
A novel online algorithm to segment multiple objects in a video sequence is proposed in this work. We develop the collaborative detection, tracking, and segmentation (CDTS) technique to extract multiple segment tracks accurately. First, we jointly use object detector and tracker to generate multiple bounding box tracks for objects. Second, we transform each bounding box into a pixel-wise segment,...
Extending state-of-the-art object detectors from image to video is challenging. The accuracy of detection suffers from degenerated object appearances in videos, e.g., motion blur, video defocus, rare poses, etc. Existing work attempts to exploit temporal information on box level, but such methods are not trained end-to-end. We present flow-guided feature aggregation, an accurate and end-to-end learning...
Recent approaches for high accuracy detection and tracking of object categories in video consist of complex multistage solutions that become more cumbersome each year. In this paper we propose a ConvNet architecture that jointly performs detection and tracking, solving the task in a simple and effective way. Our contributions are threefold: (i) we set up a ConvNet architecture for simultaneous detection...
The Compact Muon Solenoid (CMS) experiment at CERN is scheduled for a major upgrade in the next decade in order to meet the demands of the new High Luminosity Large Hadron Collider. Amongst others, a new tracking system is under development including an outer tracker capable of rejecting low transverse momentum particles by looking at the coincidences of hits (stubs) in two closely spaced sensor layers...
Infrared (IR) guided missiles remain a threat to both military and civilian aircraft, and as such, the development of effective countermeasures against this threat remains vital. A simulation has been developed to assess the effectiveness of a jammer signal against a conical-scan seeker by testing critical jammer parameters. The critical parameters of a jammer signal are the jam-to-signal (J/S) ratio,...
Adaptive tracking-by-detection approaches are popular for tracking arbitrary objects. They treat the tracking problem as a classification task and use online learning techniques to update the object model. However, these approaches are heavily invested in the efficiency and effectiveness of their detectors. Evaluating a massive number of samples for each frame (e.g., obtained by a sliding window)...
This paper presents the current state of a novel event-based surveillance framework for real-time detection and tracking of the person-of-interest with IP PTZ network camera. Formulating the problem in a (non-linear) Bayesian filtering framework in combination with Convolutional Neural Networks (CNN), we develop dynamical and adaptive approaches for identifying the Person-of-Interest(PoI) from its...
Nowadays the task of tracking pedestrians is often addressed within a tracking-by-detection framework, which in most cases entails that the position of each target has been detected before tracking begins. However in some cases, a pedestrian who is being tracked may be obscured by other targets or obstacles, and during this period they may change their trajectory or speed (track drift), and sometimes...
People with disabilities who cannot move their whole body need other people to control the smart wheelchair or track the moving of object interest, in this case people. In this paper, we have proposed new movement controller of smart wheelchair using object tracking for disabled people who cannot move their whole body. The proposed method for determining direction of moving object using object tracking...
This paper presents an online multiple pedestrian detection and tracking method using unified multi-channel features. The proposed method efficiently utilizes the multi-channel features by sharing them in each module: pedestrian detection, visual tracking, and data association. The multi-channel features are originally generated from the pedestrian detection module, and they represent sufficiently...
In object tracking, a novel tracking framework which is called “Tracking-Leaning-Detection” was proposed by Zdenka Kalal. This framework decomposes the object tracking task into tracking, learning and detection. In every frame that follows, the tracker and the detector work simultaneously to obtain the location of the object independently, and the learning acts as an information exchanging center...
This paper presents a low-complexity two-dimensional (2D) detection strategy for shingled magnetic recording (SMR) media. The detection strategy involves the use of multi-level 2D BCJR detector along-track for inter-symbol interference (ISI) cancellation and regular BCJR detector across tracks for inter-track interference (ITI) cancellation. This is applied in a multi-track two dimensional magnetic...
Tracking-by-detection has become a popular tracking paradigm in recent years. Due to the fact that detections within this framework are regarded as points in the tracking process, it brings data association ambiguities, especially in crowded scenarios. To cope with this issue, we extended the multiple hypothesis tracking approach by incorporating a novel enhancing detection model that included detection-scene...
As a response to rapidly increasing costs due to congestion in urban traffic environments, the development of Intelligent Transport Systems (ITS) has paved the way towards new and innovative mobility concepts. With most of these concepts offering benefits in travel time and congestion relief, they also come with requirements of a fully participating vehicle network and a centralized routing architecture...
Nowadays, HOG (Histogram of Gradient) feature is extracted from the objects and using it in the classification tasks among the many visual application systems such as object tracking, action recognition and automated video surveillance. Most techniques of extraction HOG feature are based on cells and blocks. Although the HOG feature on cell and block are being robust for current visual systems, the...
Although the classic TLD (tracking-learning-detection) target tracking algorithm can track a single target robustly in a long period, its real-time performance is poor. CT (Compressing Tracking) real-time tracking algorithm is real-time and efficient, but it cannot accurately track the scale-changing targets. Aiming at handling both methods' shortcomings, this paper proposes an improved TLD tracking...
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.