Uniformly minimum variance unbiased estimation for asynchronous event-based cameras

机译：基于异步事件的摄像机的一致最小方差无偏估计

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Asynchronous event-based cameras use time encoding to code the pixel intensity values. A time encoding of a random valued pixel is a representation of the intensity of this pixel as a random sequence of strictly increasing times. The goal of this paper is the estimation of the pixel mean value from asynchronous samples given by the integrate and fire time encoding. The optimal uniformly minimum variance unbiased estimator is calculated and its statistical performance is compared with a conventional frame-based estimator which exploits regular samples of the pixel intensity. Time encoding significantly reduces the mean number of bits needed to minimize the mean square error of the estimate. Hence, time encoding saves power compared to regular sampling.

机译：基于事件的异步摄像机使用时间编码来编码像素强度值。随机值像素的时间编码是该像素的强度表示为严格增加时间的随机序列。本文的目的是从积分和触发时间编码给出的异步样本中估计像素均值。计算最佳均匀最小方差无偏估计器，并将其统计性能与利用像素强度规则样本的常规基于帧的估计器进行比较。时间编码大大减少了使估计的均方误差最小所需的平均位数。因此，与常规采样相比，时间编码可以节省功耗。

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《IEEE International Conference on Image Processing》|2014年|4107-4111|共5页
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Fillatre Lionel; Antonini Marc;
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cameras; estimation theory; image coding; image representation; image sampling; mean square error methods; random sequences; statistical analysis; asynchronous event-based camera; asynchronous sampling; fire time encoding; frame-based estimator; intensity representation; mean square error minimization; optimal uniformly minimum variance unbiased estimator; pixel intensity value encoding; pixel mean value estimation; random sequence; statistical performance; Cameras; Delays; Encoding; Estimation; Neuromorphics; Random variables; Sensors; Event-based camera; Integrate and fire sampler; Statistical estimation; Time encoding;

机译：相机;估计理论;图像编码;图像表示;图像采样;均方误差方法;随机序列;统计分析;基于事件的异步相机;异步采样;触发时间编码;基于帧的估计器;强度表示;均方误差最小化最优均匀最小方差无偏估计器;像素强度值编码;像素均值估计;随机序列;统计性能;相机;延迟;编码;估计;神经形态学;随机变量;传感器;基于事件的相机;集成和采样器;统计估计;时间编码;

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1. Uniformly minimum variance conditionally unbiased estimation in multi-arm multi-stage clinical trials [J] . Stallard Nigel, Kimani Peter K. Biometrika . 2018,第2期

机译：均匀的最小方差有条件地在多臂多阶段临床试验中无偏见的估计
2. MAXIMUM LIKELIHOOD AND UNIFORMLY MINIMUM VARIANCE UNBIASED ESTIMATION OF P(Y [J] . Wasi Alam, Ajit Chaturvedi, K N. Singh, International Journal of Agricultural and Statistical Sciences . 2014,第2期

机译：Gompertz分布的P（Y
3. Uniformly minimum variance nonnegative quadratic unbiased estimation in a generalized growth curve model [J] . Wu XY, Zou GH, Li YF Journal of Multivariate Analysis: An International Journal . 2009,第5期

机译：广义增长曲线模型中的一致最小方差非负二次无偏估计
4. Uniformly minimum variance unbiased estimation for asynchronous event-based cameras [C] . Fillatre Lionel, Antonini Marc IEEE International Conference on Image Processing . 2014

机译：均匀的最小方差对基于异步事件的相机的无偏见估计
5. On Minimum Variance Unbiased Estimation of a Power Of an Unknown Scalar or Matrix. [D] . Smith, Kathleen Elise. 2017

机译：关于最小方差的未知标量或矩阵的幂的无偏估计。
6. Optical Flow Estimation by Matching Time Surface with Event-Based Cameras [O] . Jun Nagata, Yusuke Sekikawa, Yoshimitsu Aoki 2021

机译：通过匹配基于事件的相机的时间表面来估计光学流量估计
7. Uniformly minimum variance conditionally unbiased estimation in multi-arm multi-stage clinical trials [O] . Stallard, Nigel, Kimani, Peter K. 2018

机译：多臂多阶段临床试验中的一致最小方差有条件无偏估计
8. On the Uniformly Minimum Variance Unbiased Estimators of the Variance and its Reciprocal of an Inverse Gaussian Distribution [R] . Korwar, R. M. 1979

机译：关于逆高斯分布的方差的一致最小方差无偏估计及其倒数

Uniformly minimum variance unbiased estimation for asynchronous event-based cameras

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