A Control Architecture for Time‐Optimal Landing of a Quadrotor Onto a Moving Platform

We address the problem of autonomous landing of a quadrotor onto a heaving (moving vertically) platform in this paper. A control architecture that consists of a motion estimation module, a trajectory generation module and a tracking control module is proposed. The motion estimation module estimates the absolute motion of the platform and the quadrotor with the measurements from an on‐board accelerometer and vision measurements. Based on these estimates, the trajectory generation module generates a time‐optimal reference trajectory. With the reference trajectory and motion estimation, the tracking control module synthesizes a control command that enables robust tracking of the reference trajectory. Experimental results and comparison with a state‐of‐the‐art landing controller demonstrate the effectiveness of the proposed control architecture.     

HDS, a real-time multi-DSP motion estimator for MPEG-4 H.264 AVC high definition video encoding

H.264 AVC video compression standard achieves high compression rates at the cost of a high encoder complexity. The encoder performances are greatly linked to the motion estimation operation which requires high computation power and memory bandwidth. High definition context magnifies the difficulty of a real-time implementation. EPZS and HME are two well-known motion estimation algorithms. Both EPZS and HME are implemented in a DSP and their performances are compared in terms of both quality and complexity. Based on these results, a new algorithm called HDS for Hierarchical Diamond Search is proposed. HDS motion estimation is integrated in a AVC encoder to extract timings and resulting video qualities reached. A real-time DSP implementation of H.264 quarter-pixel accuracy motion estimation is proposed for SD and HD video format. Furthermore HDS characteristics make this algorithm well suited for H.264 SVC real-time encoding applications.     

Volterra series analysis and synthesis of a neural network forvelocity estimation

The motion detection problem occurs frequently in many applications connected with computer vision. Researchers have studied motion detection based on naturally occurring biological circuits for over a century. In this paper, we propose and analyze a motion detection circuit which is based on nerve membrane conduction. It consists of two unidirectional neural networks connected in an opposing fashion. Volterra input-output (I-O) models are then derived for the network so that velocity estimation can be cast as a parameter estimation problem. The technique is demonstrated through simulation.     

Real-time motion estimation for image and video processing applications

This contribution focuses on different topics that are covered by the special issue titled “Real-Time Motion Estimation for image and video processing applications” and which incorporate GPUS, FPGAs, VLSI systems, DSPs, and Multicores, among other platforms. The guest editors have solicited original contributions, which address a wide range of theoretical and practical issues related to high-performance motion estimation image processing including, but not limited to: real-time matching motion estimation systems, real-time energy-based motion estimation systems, gradient-based motion estimation systems, optical flow estimation systems, color motion estimation systems, multi-scale motion estimation systems, optical flow and motion estimation systems, analysis or comparison of specialized architectures for motion estimation systems and real-world applications.     

Block motion estimation using adaptive modified two-bit transform

An adaptive modification to the two-bit transform-based low-complexity block motion estimation approach is proposed. Initially, video frames are converted into two-bit representations using the two-bit transform (2BT), and binary block-based motion estimation is performed using these two bit-planes. Modification to the original 2BT-based motion estimation scheme is introduced by conditional local or full searches using the mean absolute difference criterion to improve the initial motion estimation accuracy. The condition threshold is adaptively varied according to block detail using the block variance already computed for the 2BT process. Experimental results show that the proposed adaptive modified 2BT-based motion estimation technique can significantly improve peak signal-to-noise ratio performance compared with 2BT only motion estimation, and outperforms modified one-bit transform (1BT)-based motion estimation as well as modified 2BT-based motion estimation without adaptation at the same motion estimation cost. The main contribution of this work is to provide an adaptive decision on whether a modified search should be carried out after the low-complexity motion estimation process.     

一种基于新型遗传算法的块运动估计算法

提出了一种基于新型遗传算法的块匹配运动估计算法。该算法把块运动向量作为遗传染色体,经过选择变异等操作,将随机搜索与特定目标搜索相结合,解决了以往快速搜索算法易陷于局部最优的问题,同时该算法中所带的模糊评价函数使得对个体的评价更合理、客观,该算法还将运动矢量空间偏置特性用于初始种群的选取,进一步提高了算法性能。实验结果表明,该算法性能上接近于FSA,速度却接近于TSS。     

基于分组误差的快速分数像素运动估计算法

H.264是最新一代的视频编码标准,它支持高精度分数像素运动估计。当在整数运动估计中采用快速算法后,分数像素的运动估计可能成为制约快速运动估计算法性能的瓶颈。根据匹配准则的目标函数在最优运动矢量的附近都是单调递增这一假设,提出一种基于分组误差的快速分数像素运动估计算法。实验结果表明该算法不但能够有效降低分数像素运动估计的计算量,而且还能保持较小的率失真性能损失。     

基于冗余小波变换的自适应运动估计与补偿算法研究*

为进一步提高运动估计和补偿的效果,提出了一种基于冗余离散小波变换（RDWT）的自适应运动估计算法。该算法提出了一种自适应块匹配和用于划分块运动状况的自适应阈值的计算方法;对静止块不进行估计,只对运动块采用自适应搜索起点预测方法和自适应阈值算法进行运动估计与补偿。实验结果表明,该方法能在保持较高峰值信噪比的情况下提高运动估计效率,且重建图像主观质量很好,较现有RDWT域运动估计算法有明显优势。     

运动估计与运动补偿在电子稳像中的应用

电子稳像系统的核心是运动估计和运动补偿。为了提供运动估计的精度和降低时间开销，达到实时应用的要求，该文提出了基于宏块的步进全局运动估计算法，获得图像序列的全局运动矢量；给出了一个新的应用于电子稳像系统中运动估计与运动补偿模块的运动估计、运动补偿原理框图；采用两步补偿算法完成对图像序列的运动补偿，得到稳定的图像序列输出。仿真结果表明，采用的方法是高效、可行的。     

Simultaneous Motion Detection and Background Reconstruction with a Conditional Mixed-State Markov Random Field

In this work we present a new way of simultaneously solving the problems of motion detection and background image reconstruction. An accurate estimation of the background is only possible if we locate the moving objects. Meanwhile, a correct motion detection is achieved if we have a good available background model. The key of our joint approach is to define a single random process that can take two types of values, instead of defining two different processes, one symbolic (motion detection) and one numeric (background intensity estimation). It thus allows to exploit the (spatio-temporal) interaction between a decision (motion detection) and an estimation (intensity reconstruction) problem. Consequently, the meaning of solving both tasks jointly, is to obtain a single optimal estimate of such a process. The intrinsic interaction and simultaneity between both problems is shown to be better modeled within the so-called mixed-state statistical framework, which is extended here to account for symbolic states and conditional random fields. Experiments on real sequences and comparisons with existing motion detection methods support our proposal. Further implications for video sequence inpainting will be also discussed.     

The Argus eye: a new imaging system designed to facilitate robotic tasks of motion

This article describes an imaging system that has been designed to facilitate robotic tasks of motion. The system consists of a number of cameras in a network, arranged so that they sample different parts of the visual sphere. This geometric configuration has provable advantages compared to small field of view cameras for the estimation of the system's own motion and, consequently, the estimation of shape models from the individual cameras. The reason is, inherent ambiguities of confusion between translation and rotation disappear. Pairs of cameras may also be arranged in multiple stereo configurations, which provide additional advantages for segmentation. Algorithms for the calibration of the system and the three-dimensional (3-D) motion estimation are provided.     

Efficient motion vector recovery algorithm for H.264 based on a polynomial model

In this paper, we propose an efficient motion vector recovery algorithm for the new coding standard H.264, which is based on a polynomial model. To achieve better coding efficiency, the motion estimation scheme used in H.264 is different from previous coding standards. In H.264, a 16/spl times/16 macroblock can be divided into different block shapes for motion estimation. Each macroblock contains more motion vectors than previous coding standards. For nature video, the blocks within a small area likely belong to the same object, hence the motion vectors of neighboring blocks are highly correlated. Based on the correlation of neighboring motion vectors, we can use the motion vectors that are adjacent to the lost motion vectors to constitute a polynomial model, which can describe the change tendency of motion vectors within a small area. Through this model, the lost motion vectors can be predicted and the lost macroblocks can be reconstructed. Different video sequences are used to test the performance of proposed method. The simulation results show that the quality of corrupted video can be obviously improved by proposed algorithm.     

一种基于冗余小波变换的快速运动估计算法

由于冗余小波变换克服了离散小波变换的移变性,在冗余小波域进行运动估计可以达到很好的效果,其缺点是算法的时间复杂度过高。在分析视频序列的运动特性和已有的运动估计算法的基础上,提出一种快速的基于冗余小波变换的运动估计算法。在冗余小波域提取潜在运动区域并对图像块的运动剧烈程度进行划分,在此基础上对不同类型的图像块采取不同的搜索策略,从而减少了运动估计中不必要的搜索。实验结果表明,该方法较经典的基于冗余小波变换的运动估计算法在时间复杂度方面具有优势。     

一种基于小波分析的多分辨运动补偿视频编码器的设计

为了在甚低比特率下实现对数字视频的有效压缩和编码,提出了一种混合的多分辨运动补偿零树视频编码方案。在该编码方案中,运动矢量的获取采用了可变块大小的多分辨运动估计算法,运动估算在小波域中进行。编码器的核心部分是同基于内容的自适应量化方法相结合的预测误差帧的小波零树编码,它产生了一种具有嵌入特征的比特流,从而为精确的速率控制和基于内容的位流调节提供了可能。基于上述编码方案的实验表明:在甚低比特率下,所提出的编码方案在峰值信噪比和恢复视频的主观质量方面都具有较好的性能。     

An enhanced motion estimation approach using a genetic trail bounded approximation for H.264/AVC codecs

Genetic algorithm-based motion estimation schemes play a significant role in improving the results of H.264/AVC standardization efforts when addressing conversational and non-conversational video applications. In this paper, we present a robust motion estimation scheme that uses a noble genetic trail bounded approximation (GTBA) approach to speed up the encoding process of H.264/AVC video compression and to reduce the number of bits required to code frame. The proposed algorithm is utilized to enhance the fitness function strength by integrating trail information of motion vector and sum of absolute difference (SAD) information into a fitness function. Experimental results reveal that the proposed GTBA resolves conflict obstacles with respect to both the number of bits required to code frames and the execution time for estimation.     

Estimating nonmeasurable coordinates of elastic oscillations for large space constructions with a gyroforce engine

We develop a mathematical model for the angular motion dynamics of a large-scale space construction with a gyroforce engine, in which coordinates of the construction’s elastic oscillations are fully observable. This lets us design a joint estimation algorithm for angular motion coordinates and elastic oscillations for orientation control and angular stabilization of the construction in question. We show mathematical modeling results for the synthesized estimation algorithm that support its high accuracy, convergence, and stability.     

A new image motion estimation algorithm based on the EM technique

This paper focuses on the presentation and implementation of a new iterative algorithm for image motion coefficient estimation from noisy measurements based on the expectation-maximization (EM) technique. We also compare this algorithm with two other robust iterative algorithms. We represent the motion field by a (unitary) series expansion to obtain the motion coefficients, and show this characterization to have several virtues. First, an inherent property of motion, referred to as smoothness, is imposed. Second, the nonuniform motion estimation is reduced to the estimation of a few coefficients using the low-pass property of the motion. Finally, the motion estimation can be accomplished without the need for a motion model; in the events for which the motion model is completely unknown, the DCT representation is shown to be very effective in describing the true motion     

基于有效运动矢量识别的提前终止算法

为提高H264编码器中运动估计的速度,提出一种提前识别出有效运动矢量来简化运动搜索过程的快速运动估计算法。在统计分析四种预测运动矢量的预测准确率基础上,算法通过判别预测运动矢量之间的关系,有针对性地设置自适应阈值,从而较快识别出有效运动矢量,终止无效的运动搜索。实验结果表明,应用在UMHexagons算法和Simplified UMHexagons算法中,可以将运动估计时间分别节省19%60%和17%45%,且对图像质量和码率影响不大。     

基于度量矩阵特征值的图像空间关系描述

构造了在平移缩放旋转下保持不变的基于度量矩阵特征值的图像空间关系描述子。理论计算和仿真实验表明这种描述与人的主观视觉心理相一致,在平移缩放旋转下以及小噪声下具有较强的鲁棒性,具有较好的类别可分离性。与传统的空间关系描述方法如几何法和图匹配法相比,可以更好地描述图像空间关系,同时计算量有所减小。用于图像识别、图像检索、图像配准取得了较好效果。     

COM motion estimation of a biped robot based on kinodynamics and torque equilibrium

A novel technique to estimate motion of the center of mass (COM) for a biped robot is proposed. A Kalman filter is synthesized where the time evolution of COM is predicted from the external force and corrected based on kinematic estimation and torque equilibrium. They complementarily work to compensate the initial estimation offset, the error accumulation, and errors in modeled mass properties. It makes use of the authors’ previous method to estimate the translational and rotational motion of the base body from inertial information and joint angle measurements. The information about torque equilibrium helps to reduce an uncertainty of the height of COM and to improve the estimation accuracy of it by utilizing an interference of the horizontal and vertical motion of COM. The parameters are tuned based on error analyses in mass properties and sensor signals. A comparative study showed a better performance of the proposed method than other methods through dynamics simulations.