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.
Trajectory analysis is very important to human behavior-analysis for video processing based smart surveillance systems. It has a challenge that human trajectory has no prior model and needs to online learning and updating, while interaction between targets complicates the problem. This paper describes a novel integrated framework for multiple human trajectory detection, learning and analysis in complicated...
In this paper, we propose a Hamiltonian Markov Chain Monte Carlo based tracking algorithm for abrupt motion tracking within the Bayesian filtering framework. In this tracking scheme, the object states are augmented by introducing a momentum item and the Hamiltonian Dynamics (HD) is integrated into the traditional MCMC based tracking method. The HD has some excellent properties which are crucial in...
In this paper, we present a method of robust tracking by accounting for hard negatives (i.e., distractors) of the tracking target explicitly. Our method extends the recently proposed Tracking-Learning-Detection (TLD) approach [7] in two aspects: (i) When learning the on-line fern detector, instead of using a set of features which are first randomly generated and then fixed throughout the tracking,...
Recently many appearance based visual tracking algorithms have been investigated, aimed at building robust appearance models against challenges brought by the varying appearance of the target as well as the unconstrained environment. More often adaptive appearance models were used to capture these variances over time, but this may sometimes result in losing the target (drifting) due to inappropriate...
We propose an approach for multi-pose face tracking by association of face detection responses in two stages using multiple cues. The low-level stage uses a two-threshold strategy to merge detection responses based on location, size and pose, resulting in short but reliable tracklets. The high-level stage uses different cues for computing a joint similarity measure between tracklets. The facial cue...
We introduce a semi-automatic tracking method that can be utilized for the analysis of facial markers in the medical condition of facial palsy. Tracking of markers will help medical physicians in evaluating this medical condition quantitatively. We use particle filtering to track markers towards measuring distances needed to evaluate the degree of facial palsy. We show that by employing tracking methods,...
We propose a fast and efficient method for localization and rectification of a dominant rectangular region within an image, particularly suitable for mobile Augmented Reality applications. This approach can deal with perspective distortion and high-frequency structures such as text. The resulting image may be used for planar tracking or as input for subsequent image processing tasks. We demonstrate...
Spatial augmented reality extends augmented reality by projecting virtual data directly on a target surface, but requires to calibrate a projector-camera system. This paper introduces a free-calibration projector-camera system for spatial augmented reality with a planar surface. A pattern is projected on the target surface that can be freely moved. The main difficulty is to make the projected image...
Visual object tracking in video can be formulated as a time varying appearance-based binary classification problem. Tracking algorithms need to adapt to changes in both foreground object appearance as well as varying scene backgrounds. Fusing information from multimodal features (views or representations) typically enhances classification performance without increasing classifier complexity when image...
This paper presents a modified Kanade-Lucas-Tomasi (KLT) tracking framework for multiple objects tracking applications. First, the framework includes a global pixel-level probabilistic model and an adaptive RGB template model to modify traditional KLT tracker more robust to track multiple objects and partial occlusions. Meanwhile, a Merge and Split algorithm is introduced in the proposed framework...
This paper proposes a new version of Particle Filter, called Articulated Particle Filter — ArPF —, which has been specifically designed for an efficient sampling of hierarchical spaces, generated by articulated objects. Our approach decomposes the articulated motion into layers for efficiency purposes, making use of a careful modeling of the diffusion noise along with its propagation through the articulations...
This paper describes a method of tracking multiple persons with occlusions using stereo. We previously developed an accurate and stable tracking method using overlapping silhouette templates which considers how persons overlap in the image. It realized a fast tracking by using an approximated likelihood map based on kernel density estimation. The method, however, treated only two overlapping persons...
In this paper, we propose an adaptive particle filter method based on the cross-bin matching, which makes use of the fast and robust earth mover's distance with a thresholded ground distance (EMD) as the similarity measure, for robust visual tracking. In contrast to the traditional bin-by-bin metrics, the cross-bin metric used in the EMD is capable of efficiently capturing the intrinsic affinity relationships...
Model based tracking approaches estimate the pose of the object by minimizing the re-projection error. However, when the object has some ambiguity, for instance, rotation invariance, the 3D pose cannot be correctly estimated. This paper proposes a novel method to allow continuous tracking even when the Degrees of Freedom (DoF) of the target object changes, being able to recover one missing DoF. Pose...
In this paper we present an effective and fast tracking algorithm, in which object tracking is achieved by solving L2-regularized least square (L2-RLS) problem-s within a Bayesian inference framework. Firstly, we model the appearance of the tracked target with P-CA basis vectors and square templates which make the tracker not only exploit the strength of sub space repre-senation but also explicitly...
To deal with the drifting issue in visual tracking, we propose an Online Transfer Boosting (OTB) algorithm that transfers knowledge from three different source domains to the target domain to improve the performance of the online classifier used in tracking-by-detection. In particular, the OTB algorithm integrates three types of knowledge by: (1) transferring prior knowledge from the first frame using...
In this paper, we consider the multi-camera tracking and the camera active control (pan and tilt). Auction mechanism from economics is developed to choose the best available camera. By modeling the camera bids with prior knowledge of the camera homographies, the system can “think” ahead to perform necessary panning or tilting operations. The uncertainties of homographies are considered inherently...
Accurate segmentation provides a useful contour constraint to alleviate drifting during online learning for tracking. Towards this end, we present a closed-loop method for object tracking that links Hough forests and alpha matting via an effective back-projection scheme for patches. A novel hybrid-Hough-forests-based method first estimates object location. Given the object location, the trimap of...
In this paper we present a technique for real-time face logging in video streams. Our system is capable of detecting faces across a range of poses and of tracking multiple targets in real time, grabbing face images and evaluating their quality in order to store only the best for each detected target. An advantage of our approach is that we qualify every logged face in terms of a quality measure based...
In the paper, we present an approach to efficiently summarizing UAV video data. Our approach is based on first detecting and tracking moving objects. Significant camera motion usually present in UAV video data is successfully handled by a robust feature-based frame registration technique. We then devise a saliency-based scoring method to score and rank detected object tracks. Object tracks are then...
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.