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.
It is significant to have accurate localization of surgical instruments in navigated minimally invasive surgery. Moreover, instrument tracking modules are essential for cognitive surgical robotic systems. Commercial optical trackers have been developed with sub-millimeter accuracy, but typically work only at single spectrum — either visible spectrum or infrared spectrum, which limits the sensing and...
Visual tracking is challenging due to appearance changes caused by motion, illumination, occlusion and pose, among others. For these local changes, appearance model based tracking algorithms, such as MILtracker [8], have adopted local features and most recently extended to compressive domain, namely Compressive Tracking [13], for the real-time performance. However, the motion information is missed...
This paper proposes a new method to find face in real-time videos by combining detection and tracking. Basically, the method contains two complementary modules: detection by Viola Jones method and tracking by correlation filters. Detection in current frame is independent to previous frames, but the performance may downgrade under harsh conditions in terms of lighting, rotation, occlusion and others...
Based on the Lucas-Kanade optical flow method, a dynamically selecting model is proposed in this paper to track a moving object. This model is composed of an object model, a consistency constraint model, and a random sampling model. Based on the current image frame, the object model is used to calculate the relevant feature points for the next frame. The random sampling model is used to resample the...
We propose a multi-person tracking framework using only one single camera in this paper. We utilize particle filter as the tracking framework and train a SVM classifier by reliable examples extracted from associated detections without occlusion. Based on the results of data association, we integrate the target's velocity into weights calculation to handle object occlusion assuming that fast-moving...
Registration is a key issue in image-guided minimally invasive vascular surgery (MIVS) when the electromagnetic device is used to tracking the catheter. We assume that the catheter advances in the vessel along the vascular centerline during MIVS. Based on this assumption, we proposed a dynamic point matching approach for registration, of which the transformation is estimated by aligning the point...
As the acoustic images are low-quality, it is difficult to use these images for scientific research and practical applications directly. Although the PSNR of sonar images were improved through existing methods, denoised images were lack of clarity so that the outline of objects and details had not been better preserved. Subsequently, this impacted accuracy of target detection. In this paper, we propose...
Our bionic eye PTZ requires the tracking target at the central field of view of the camera, which means it is so important to realize the target tracking well in the first step. The particle filter method is famous for its robust tracking performance in cluttered environments. However, most methods are in the mode of moving object and stationary camera and they are not utilizing so well on the bionic...
Visual tracking is challenging due to appearance changes caused by motion, illumination, occlusion and pose, among others. For these local changes, appearance model based tracking algorithms, such as MILtracker [8], have adopted local features and most recently extended to compressive domain, namely Compressive Tracking [13], for the real-time performance. However, the motion information is missed...
This paper presents a fuzzy-based intelligent control strategy allowing a mobile robot to safely follow a given person. The robot is embedded with two sensors: a RFID and a stereo camera. The RFID can locate the given person with an ID tag, and the stereo camera can be used to detect the target. Based on the two sensors, a robust control strategy is designed according to the target's speed and his...
Detection and Tracking of human being is a very important problem in Computer Vision. Human robot interaction is a very essential need for service robots where robots are required to detect and track human beings in order to provide the required service. In this paper we present an improved novel approach for tracking a target person in crowded environment. We used multi-sensor data fusion approach...
We propose a novel tracking algorithm based on insect vision inspired particle filter. In a cluttered moving background, flying insects demonstrate extraordinary capability in locating and detecting visual objects. Our tracker introduces an Elementary Motion Detector (EMD) which is deduced from the neuronal computational model of the way biological ommateum processing information, and integrates the...
In this paper, we propose online metric learning tracking method that consider visual tracking as a similarity measurement problem, and incorporates adaptive metric learning and generative histogram model based on non-sparse linear representation into the target tracking framework. We propose a generative histogram model based on non-sparse linear representation, which make full use of the non-sparse...
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.