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Computer Vision and Image Understanding, 2011
Accurate feature tracking is the foundation of many high level tasks in computer vision, such as 3D reconstruction and motion analysis. Although there are many feature tracking algorithms, most of them do not maintain information about the error of the data being tracked. Also, due to the difficulty and spatial locality of the problem, existing methods
Leyza Baldo Dorini +1 more
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Accurate feature tracking is the foundation of many high level tasks in computer vision, such as 3D reconstruction and motion analysis. Although there are many feature tracking algorithms, most of them do not maintain information about the error of the data being tracked. Also, due to the difficulty and spatial locality of the problem, existing methods
Leyza Baldo Dorini +1 more
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Track-to-track association for tracks with features and attributes
SPIE Proceedings, 2005The problem of track-to-track association - a prerequisite for fusion of tracks - has been considered in the literature only for tracks described by kinematic states. The association of tracks from a common target can also be solved using additional feature or attribute variables which are associated with those tracks. We extend the existing results to
Yaakov Bar-Shalom, Huimin Chen
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Hand Tracking with Flocks of Features
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005Tracking hands in live video is a challenging task: the hand appearance can change too rapidly for appearance-based trackers to work, and color-based trackers (that do not rely on geometry) have to make limiting assumptions about the background color.
Mathias Kölsch, Matthew Turk 0001
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Feature Association for Object Tracking
2006 9th International Conference on Information Fusion, 2006This paper addresses the problem of feature-based estimation of the 3D motion (rotational + translational) and structure of a rigid object from a sequence of 2D monocular images. A rigid object is represented by a set of junctions?groupings of line segments that meet at a single point?which has several advantages over other techniques.
Vesselin P. Jilkov +3 more
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Learning Good Features to Track
2014 13th International Conference on Machine Learning and Applications, 2014Object tracking is an important task within the field of computer vision. Tracking accuracy depends mainly on finding good discriminative features to estimate the target location. In this paper, we introduce online feature learning in tracking and propose to learn good features to track generic objects using online convolutional neural networks (OCNN).
Raed Almomani, Ming Dong 0001, Zhou Liu
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Robust Facial Feature Tracking
Procedings of the British Machine Vision Conference 2000, 2000We present a robust technique for tracking a set of pre-determined points on a human face. To achieve robustness, the Kanade-Lucas-Tomasi point tracker is extended and specialised to work on facial features by embedding knowledge about the configuration and visual characteristics of the face.
Fabrice Bourel +2 more
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Multi-feature Hashing Tracking
Pattern Recognition Letters, 2016The hashing method is introduced into tracking algorithm.2D fusion hashing is proposed to get robust binary feature of object.An effective and easy-to-update model is designed for online updating.The influence of different settings on our tracker is evaluated.
Chao Ma 0002 +3 more
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Motion tracking of iris features for eye tracking
Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications, 2019Current video-based eye trackers fail to acquire a high signal-to-noise (SNR) ratio which is crucial for specific applications like interactive systems, event detection, the study of various eye movements, and most importantly estimating the gaze position with high certainty.
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Feature-aided particle tracking
2008 15th IEEE International Conference on Image Processing, 2008We present a new feature-aided tracking algorithm dedicated to the task of tracking multiple and closely-spaced biological particles. We propose a new function to score associations, based on kinetic models, and enriched with an additional feature. This feature is based on adaptive profiles and the physical properties of the acquisition system.
Nicolas Chenouard +2 more
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Natural feature tracking in JavaScript
2012 IEEE Virtual Reality (VR), 2012We present an efficient natural feature tracking pipeline solely implemented in JavaScript. It is embedded in a web technology-based Augmented Reality system running plugin-free in web browsers. The evaluation shows that real-time framerates on desktop computers and while on smartphones interactive framerates are achieved.
Christoph Oberhofer +2 more
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