Fluctuations in closed-loop fluorescent particle tracking
نویسندگان
چکیده
منابع مشابه
Fluctuations in closed-loop fluorescent particle tracking.
We present a comprehensive theory of closed-loop particle tracking for calculating the statistics of a diffusing fluorescent particle's motion relative to the tracking lock point. A detailed comparison is made between the theory and experimental results, with excellent quantitative agreement found in all cases. A generalization of the theory of (open-loop) fluorescence correlation spectroscopy ...
متن کاملClosed-Loop Adaptation for Robust Tracking
Model updating is a critical problem in tracking. Inaccurate extraction of the foreground and background information in model adaptation would cause the model to drift and degrade the tracking performance. The most direct but yet difficult solution to the drift problem is to obtain accurate boundaries of the target. We approach such a solution by proposing a novel closed-loop model adaptation f...
متن کاملA closed-loop approach for tracking a humanoid robot using particle filtering and depth data
Humanoid robots introduce instabilities during biped march that complicate the process of estimating their position and orientation along time. Tracking humanoid robots may be useful not only in typical applications such as navigation, but in tasks that require benchmarking the multiple processes that involve registering measures about the performance of the humanoid during walking. Small robot...
متن کاملObject Tracking and Segmentation in a Closed Loop
We introduce a new method for integrated tracking and segmentation of a single non-rigid object in an monocular video, captured by a possibly moving camera. A closed-loop interaction between EM-like color-histogram-based tracking and Random Walker-based image segmentation is proposed, which results in reduced tracking drifts and in fine object segmentation. More specifically, pixel-wise spatial...
متن کاملClosed-loop Servoing using Real-time Markerless Arm Tracking
We present a simple, efficient method of realtime articulated arm pose estimation using stochastic gradient descent to correct unmodeled errors in the robot’s kinematics with point cloud data from commercial depth sensors. We show that our method is robust to error in both the robot’s joint encoders and in the extrinsic calibration of the sensor; and that it is both fast and accurate enough to ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Optics Express
سال: 2007
ISSN: 1094-4087
DOI: 10.1364/oe.15.007752