Translational Motion Model Research Articles

Insight into the critical morphological characteristics of earthquake-induced sequential rock avalanches in weathered-fractured rock cliffs

Rock avalanches are a significant threat to transportation or hydraulic infrastructure, as they can also cause catastrophic secondary destruction in large practical engineering or to nearby residents. Earthquake-induced rock avalanches have been the most common and prominent natural hazard phenomena among geological hazards in recent years. Earthquake-induced rock avalanche events usually begin when a massive rock mass or multiple rock masses separate from a rock slope, progressively fragmenting and transforming into fast-moving, cohesionless rock falls. Earthquake-induced sequential collapse often occurs on weathered and fractured rock cliffs in horizontal strata, and its kinematic dynamics and destabilization mechanism are significantly different from those of isolated collapse due to weathering. In this study, the failure characteristics of the initiation and movement process of the avalanche are revealed in detail, through physical model experiments and analytical solutions, thereby obtaining an earthquake-controlled mechanical model equation. Our methods use the inflection points of the displacement time curve at the top of the rock wall and the digital images acquired by the shaking test bench to quantify the critical damage time point and to characterize the critical morphology of continuous collapse. A mathematical model of analytical solution is proposed, which aims to address the kinematic mechanics mechanism of sequential collapse under translational and rotational motion models. The comparative analysis results of the experiment and analytical solutions reveal that the transformed motion pattern is controlled by the ratio between the model stacking height, the rock block size, and the seismic acceleration. Whereas the rotational motion pattern is mainly influenced by the nodal dip angle, model stacking height, and seismic acceleration. The results of the study are of great scientific importance to elucidate the destruction mechanism of the earthquake-induced sequential collapse of rock avalanches and to determine the evolution characteristic of subsequent rockfalls motion of dangerous rocks. The proposed framework for the analysis of rock avalanches can be applied to understand the critical topographic features and mechanical mechanism behavior of analogous geological hazards.

A Two-Step Discrete Cosine Basis Oriented Motion Modeling Approach for Enhanced Motion Compensation.

Video coding algorithms attempt to minimize the significant commonality that exists within a video sequence. Each new video coding standard contains tools that can perform this task more efficiently compared to its predecessors. Modern video coding systems are block-based wherein commonality modeling is carried out only from the perspective of the block that need be coded next. In this work, we argue for a commonality modeling approach that can provide a seamless blending between global and local homogeneity information in terms of motion. For this purpose, at first a prediction of the current frame, the frame that need be coded, is generated by performing a two-step discrete cosine basis oriented (DCO) motion modeling. The DCO motion model is employed rather than traditional translational or affine motion model since it has the ability to efficiently model complex motion fields by providing a smooth and sparse representation. Moreover, the proposed two-step motion modeling approach can yield better motion compensation at a reduced computational complexity since an informed guess is designed for initializing the motion search procedure. After that the current frame is partitioned into rectangular regions and the conformance of these regions to the learned motion model is investigated. Depending on the non-conformance to the estimated global motion model, an additional DCO motion model is introduced to increase the local motion homogeneity. In this way, the proposed approach generates a motion compensated prediction of the current frame through the minimization of both global and local motion commonality. Experimental results show an improved rate-distortion performance of a reference high efficiency video coding (HEVC) encoder, specifically up to around 9% savings in bit rate, that employs the DCO prediction frame as a reference frame for encoding the current frame. When compared to the more recent video coding standard, the versatile video coding (VVC) encoder, a bit rate savings of 2.37% is reported.

An efficient six-parameter perspective motion model for VVC

Tilt and pan camera movements are common in computer games or social media videos. These types of videos contain numerous perspective transforms while today’s video codecs rely on translational and affine motion models for motion compensation. The general perspective motion model with 8 parameters (8PMM) has unreasonably high processing time. In this paper, the eight-parameter perspective transform is simplified into a six-parameter transform to keep the time complexity within an acceptable range while modeling the most relevant transforms. Also, two motion prediction modes, Advanced Perspective Motion Vector Prediction (APMVP) and Perspective Model Merge (PMM), are proposed. The implementation results show an average of 7.0% BD-rate reduction over H.266/VVC Test Model with a maximum of 20% encoding time overhead. The results also show a 71% processing time reduction in comparison to 8PMM while experiencing an average of 5.6% increase in BD-Rate. Much better visual quality is measured through VMAF quality meter.

A Robust Translational Motion Compensation Method Based on Weighted Optimization Framework—Second-Order Drift Particle Swarm Optimization

Accurate translational motion compensation is critical for ISAR imaging, especially for datasets with low signal-to-noise ratio (SNR) or sparse aperture. Among the existing translational motion compensation methods, the methods that based on the polynomial model have profound noise robustness but are easily affected by the variation of the reference distance. The methods that based on the range profile alignment have good versatility but are far from ideal under low SNR and sparse aperture environment. Therefore, we propose a novel and robust translational motion compensation method to overcome the shortcoming of the existing methods. Specifically, we estimate the translational phase error sequence by maximizing Laplacian average gray level and peak value. It can improve the robustness of translational motion compensation for noise and sparse aperture. Since such principle creates a large-scale multi-objective optimization problem, we design weighted optimization framework - second-order drift particle swarm optimization (WOF - SDPSO) to solve it accurately. WOF-SDPSO achieves full exploration of high-dimensional variable space by variable dimension reducing, random drift update, and second-order oscillation convergence. These ensure the global optimal solution easier to be found. Experimental results of the measured dataset prove that the proposed method is effective and accurate under the conditions of low SNR and sparse aperture. Moreover, the proposed method is noise robust for polynomial translational motion model with sparse aperture.

Robust cascaded horizontal-plane trajectory tracking for fixed-wing unmanned aerial vehicles

This paper investigates the problem of horizontal-plane trajectory tracking for fixed-wing unmanned aerial vehicles(UAVs) subjected to external disturbances and uncertainties including coupling and unmodeled dynamics. Under the assumption there exist ideal inner-loop controllers, the 12-state model is reduced to a 6-state translational motion model, which is described by a group of simplified nonlinear equations with equivalent disturbances via introducing general aerodynamic models. Then a new cascaded control structure consisting of an outer-loop controller for position control and inner-loop controllers for attitude and thrust control is proposed. Based on feedback linearization technology and signal compensation theory, the proposed controller applied for position control incorporates a nominal linear time-invariant controller and a robust compensator, the latter of which is introduced to restrain the effects of uncertainties and disturbances. The robust performance of the closed-loop system is proved. Actual experimental results conducted on a small fixed-wing aircraft demonstrate that the proposed control approach is effective.

Experimental Research on the Similarity of Rime Icing on a Cylinder Rotating around Its Horizontal Axis

Ice accumulation on the blade of a wind turbine surface seriously threatens the operational safety of the turbine; therefore, the research on this problem is very important. In this paper, a new similarity criterion of icing shape for a rotational model was proposed based on the similarity criterion for translational motion models in the aviation field, and experimental studies on the similarity of the rotational model icing were carried out. To validate the similarity criterion, icing wind tunnel tests were carried out with aluminum cylinders with diameters of 40 mm and 20 mm. Key parameters for the experiment, such as wind speed, temperature, liquid water content, medium volume diameter, and test time, were selected based on the criterion. All the icing tests were carried out in a new self-designed icing wind tunnel test system based on natural low-temperature conditions. The icing shapes observed in the tests were confirmed after many repetitions. To quantitatively analyze the similarity between different sizes of ice shapes, a dimensionless method for evaluating the similarity of ice shapes of different sizes was defined based on the typical characteristics of ice shapes. The research results show that the similarity score between two sizes of ice shapes under different test conditions is 81%~90%. The accuracy and applicability of the icing shape similarity criterion were thus validated. The research results in this paper lay a theoretical and experimental foundation for exploring the icing shape similarity of a rotating model.

Context-Based Inter Mode Decision Method for Fast Affine Prediction in Versatile Video Coding

Versatile Video Coding (VVC) is the most recent video coding standard developed by Joint Video Experts Team (JVET) that can achieve a bit-rate reduction of 50% with perceptually similar quality compared to the previous method, namely High Efficiency Video Coding (HEVC). Although VVC can support the significant coding performance, it leads to the tremendous computational complexity of VVC encoder. In particular, VVC has newly adopted an affine motion estimation (AME) method to overcome the limitations of the translational motion model at the expense of higher encoding complexity. In this paper, we proposed a context-based inter mode decision method for fast affine prediction that determines whether the AME is performed or not in the process of rate-distortion (RD) optimization for optimal CU-mode decision. Experimental results showed that the proposed method significantly reduced the encoding complexity of AME up to 33% with unnoticeable coding loss compared to the VVC Test Model (VTM).

Side information hybrid generation based on improved motion vector field

The quality of side information has an important impact on the performance of a distributed video coding system. At present, the generation of side information is mainly based on the translational motion model using the inter-frame correlation for motion estimation. Considering that the generated side information is prone to block effect and ghosting, as well as the situation that the nonlinear motion is not fully considered and the intra-frame correlation is not fully utilized, a side information hybrid generation algorithm based on an improvement model for the motion vector field is proposed. The side information frame to be generated for the current Wyner-Ziv frame is divided into easy-to-estimate and difficult-to-estimate macroblocks. For difficult-to-estimate macroblocks, the Horn and Schunck dense optical flow method is used to generate reliable motion vectors, for easy-to-estimate macroblocks, the block matching method is used to generate unreliable motion vectors which are modified by the proposed scheme, and then, the improved motion vectors are used for motion compensation to produce the final side information frame. Experiment results show that the quality of side information obtained by using the improved motion vector field for motion compensation has been significantly improved, thus the overall performance of the distributed video coding system has been effectively improved.

Application of nanopowders in industrial production of mixed feed

One of the main directions of the feed manufacturing industry development is the improvement of the output product quality that ensures its efficacy in modern agricultural production. Some international experience in using the essential microelements in the form of nanopowders in the diets of farm animals has been gained. The article is devoted to the development and justification of a technical solution to the problem of dispensing ultrafine (nano) powders in the industrial production of combined feeds. The authors carried out theoretical and experimental studies of the influence of the conditions of functioning of industrial-technological equipment on the properties of several nanopowders of micro metals. The parametric model of the proposed pneumatic dispenser of bulk nanomaterials allows taking into account various structural and technological changes in the dosing process during the preparation of feed mixtures. The author presents a methodology for calculating the oscillatory system of a pneumatic dispenser, including an annular membrane with fixed edges, based on the equivalent replacement of a system with distributed parameters (membrane) with a system with lumped parameters, which allows replacing the oscillatory model with a translational motion model. An engineering-mathematical model that describes forced membrane oscillations, the dispenser oscillation system and the behaviour of the ultrafine material in the working chamber was constructed on its basis. Practical implementation of the results made it possible to obtain a prototype of bulk ultrafine materials dispenser.

Processing-Aware Real-Time Rendering for Optimized Tissue Visualization in Intraoperative 4D OCT.

Intraoperative Optical Coherence Tomography (iOCT) has advanced in recent years to provide real-time high resolution volumetric imaging for ophthalmic surgery. It enables real-time 3D feedback during precise surgical maneuvers. Intraoperative 4D OCT generally exhibits lower signal-to-noise ratio compared to diagnostic OCT and visualization is complicated by instrument shadows occluding retinal tissue. Additional constraints of processing data rates upwards of 6GB/s create unique challenges for advanced visualization of 4D OCT. Prior approaches for real-time 4D iOCT rendering have been limited to applying simple denoising filters and colorization to improve visualization. We present a novel real-time rendering pipeline that provides enhanced intraoperative visualization and is specifically designed for the high data rates of 4D iOCT. We decompose the volume into a static part consisting of the retinal tissue and a dynamic part including the instrument. Aligning the static parts over time allows temporal compounding of these structures for improved image quality. We employ a translational motion model and use axial projection images to reduce the dimensionality of the alignment. A model-based instrument segmentation on the projections discriminates static from dynamic parts and is used to exclude instruments from the compounding. Our real-time rendering method combines the compounded static information with the latest iOCT data to provide a visualization which compensates instrument shadows and improves instrument visibility. We evaluate the individual parts of our pipeline on pre-recorded OCT volumes and demonstrate the effectiveness of our method on a recorded volume sequence with a moving retinal forceps.

Analysis of Affine Motion-Compensated Prediction in Video Coding

Motion-compensated prediction is used in video coding standards like High Efficiency Video Coding (HEVC) as one key element of data compression. Commonly, a purely translational motion model is employed. In order to also cover non-translational motion types like rotation or scaling (zoom), e. g. contained in aerial video sequences such as captured from unmanned aerial vehicles (UAV), an affine motion model can be applied. In this work, a model for affine motion-compensated prediction in video coding is derived. Using the rate-distortion theory and the displacement estimation error caused by inaccurate affine motion parameter estimation, the minimum required bit rate for encoding the prediction error is determined. In this model, the affine transformation parameters are assumed to be affected by statistically independent estimation errors, which all follow a zero-mean Gaussian distributed probability density function (pdf). The joint pdf of the estimation errors is derived and transformed into the pdfof the location-dependent displacement estimation error in the image. The latter is related to the minimum required bit rate for encoding the prediction error. Similar to the derivations of the fully affine motion model, a four-parameter simplified affine model is investigated. Both models are of particular interest since they are considered for the upcoming video coding standard Versatile Video Coding (VVC) succeeding HEVC. Both models provide valuable information about the minimum bit rate for encoding the prediction error as a function of affine estimation accuracies.

Design of Efficient Perspective Affine Motion Estimation/Compensation for Versatile Video Coding (VVC) Standard

The fundamental motion model of the conventional block-based motion compensation in High Efficiency Video Coding (HEVC) is a translational motion model. However, in the real world, the motion of an object exists in the form of combining many kinds of motions. In Versatile Video Coding (VVC), a block-based 4-parameter and 6-parameter affine motion compensation (AMC) is being applied. In natural videos, in the majority of cases, a rigid object moves without any regularity rather than maintains the shape or transform with a certain rate. For this reason, the AMC still has a limit to compute complex motions. Therefore, more flexible motion model is desired for new video coding tool. In this paper, we design a perspective affine motion compensation (PAMC) method which can cope with more complex motions such as shear and shape distortion. The proposed PAMC utilizes perspective and affine motion model. The perspective motion model-based method uses four control point motion vectors (CPMVs) to give degree of freedom to all four corner vertices. Besides, the proposed algorithm is integrated into the AMC structure so that the existing affine mode and the proposed perspective mode can be executed adaptively. Because the block with the perspective motion model is a rectangle without specific feature, the proposed PAMC shows effective encoding performance for the test sequence containing irregular object distortions or dynamic rapid motions in particular. Our proposed algorithm is implemented on VTM 2.0. The experimental results show that the BD-rate reduction of the proposed technique can be achieved up to 0.45% and 0.30% on Y component for random access (RA) and low delay P (LDP) configurations, respectively.

Motion Estimation for Fisheye Video With an Application to Temporal Resolution Enhancement

Surveying wide areas with only one camera is a typical scenario in surveillance and automotive applications. Ultra wide-angle fisheye cameras employed to that end produce video data with characteristics that differ significantly from conventional rectilinear imagery as obtained by perspective pinhole cameras. Those characteristics are not considered in typical image and video processing algorithms such as motion estimation, where translation is assumed to be the predominant kind of motion. This contribution introduces an adapted technique for use in block-based motion estimation that takes into the account the projection function of fisheye cameras and thus compensates for the non-perspective properties of fisheye videos. By including suitable projections, the translational motion model that would otherwise only hold for perspective material is exploited, leading to improved motion estimation results without altering the source material. In addition, we discuss extensions that allow for a better prediction of the peripheral image areas, where motion estimation falters due to spatial constraints, and further include calibration information to account for lens properties deviating from the theoretical function. Simulations and experiments are conducted on synthetic as well as real-world fisheye video sequences that are part of a data set created in the context of this paper. Average synthetic and real-world gains of 1.45 and 1.51 dB in luminance PSNR are achieved compared against conventional block matching. Furthermore, the proposed fisheye motion estimation method is successfully applied to motion compensated temporal resolution enhancement, where average gains amount to 0.79 and 0.76 dB.

A Low-Complexity Mosaicing Algorithm for Stock Assessment of Seabed-Burrowing Species

This paper proposes an algorithm for mosaicing videos generated during stock assessment of seabed-burrowing species. In these surveys, video transects of the seabed are captured and the population is estimated by counting the number of burrows in the video. The mosaicing algorithm is designed to process a large amount of video data and summarize the relevant features for the survey in a single image. Hence, the algorithm is designed to be computationally inexpensive while maintaining a high degree of robustness. We adopt a registration algorithm that employs a simple translational motion model and generates a mapping to the mosaic coordinate system using a concatenation of frame-by-frame homographies. A temporal smoothness prior is used in a maximum a posteriori homography estimation algorithm to reduce noise in the motion parameters in images with small amounts of texture detail. A multiband blending scheme renders the mosaic and is optimized for the application requirements. Tests on a large data set show that the algorithm is robust enough to allow the use of mosaics as a medium for burrow counting. This will increase the verifiability of the stock assessments as well as generate a ground truth data set for the learning of an automated burrow counting algorithm.

Spherical Coordinates Transform-Based Motion Model for Panoramic Video Coding

Panoramic video is produced and displayed as if it is supported on sphere, but it is usually mapped to two-dimensional (2D) plane for compression purpose. The mapping from sphere to 2D plane inevitably causes deformation of video content, which shall be taken into account in panoramic video coding. In this paper, we propose a new motion model based on spherical coordinates transform to explicitly address the deformation problem. Different from the traditional 2D translational motion model, our model assumes a 3D translational motion, which is characterized by a 2D motion vector and a relative depth parameter. Based on spherical coordinates transform, we can deduce the motion compensation and motion estimation algorithms for our proposed motion model. We then integrate the algorithms into the joint exploration model (JEM) scheme for panoramic video coding, and perform experiments on some typical equirectangular projection format video sequences. Experimental results show that our proposed method leads to up to 10.7% and on average 2.6% BD-rate reduction compared to the JEM anchor on our test sequences, with no increase of decoding time.

An Efficient Four-Parameter Affine Motion Model for Video Coding

In this paper, we study a simplified affine motion model-based coding framework to overcome the limitation of a translational motion model and maintain low-computational complexity. The proposed framework mainly has three key contributions. First, we propose to reduce the number of affine motion parameters from 6 to 4. The proposed four-parameter affine motion model can not only handle most of the complex motions in natural videos, but also save the bits for two parameters. Second, to efficiently encode the affine motion parameters, we propose two motion prediction modes, i.e., an advanced affine motion vector prediction scheme combined with a gradient-based fast affine motion estimation algorithm and an affine model merge scheme, where the latter attempts to reuse the affine motion parameters (instead of the motion vectors) of neighboring blocks. Third, we propose two fast affine motion compensation algorithms. One is the one-step sub-pixel interpolation that reduces the computations of each interpolation. The other is the interpolation-precision-based adaptive block size motion compensation that performs motion compensation at the block level rather than the pixel level to reduce the number of interpolation. Our proposed techniques have been implemented based on the state-of-the-art high-efficiency video coding standard, and the experimental results show that the proposed techniques altogether achieve, on average, 11.1% and 19.3% bits saving for random access and low-delay configurations, respectively, on typical video sequences that have rich rotation or zooming motions. Meanwhile, the computational complexity increases of both the encoder and the decoder are within an acceptable range.

Relative State and Inertia Estimation of Unknown Tumbling Spacecraft by Stereo Vision

A novel algorithm is proposed to estimate the relative state, including position, attitude, linear velocity, angular velocity, and inertia parameters of an unknown tumbling spacecraft, by stereo vision. Feature points of the target are selected in situ , and their positions and velocities are estimated by the measurements of perspective projection and optical flow. Then, the relative attitude and angular velocity of the spacecraft are estimated by a unit quaternion method and least square method, respectively. After that, the relative position and translational velocity of the spacecraft, together with the relative positions of the detected feature points, are estimated simultaneously based on the relative translational motion model of the target by successive images. Finally, inertia parameters of the spacecraft are estimated by a quadratic optimization method based on angular momentum conservation subject to physical constraints. The performance of the newly proposed algorithm is verified by comparing with an existing case in the literature. Moreover, the performance is validated by Monte-Carlo simulations in different cases.

Merge Mode for Deformable Block Motion Information Derivation

Motion estimation (ME) plays an important role in most video coding standards since it can improve the coding performance significantly. Block matching ME (BMME) based on translation motion model is employed in both H.264/Advanced Video Coding and High Efficiency Video Coding (HEVC), which assumes that all the pixels in a block undergo the same motion. However, BMME cannot represent the complex motion accurately, such as rotation, zoom, and deformation motion. To resolve the problem, a merge mode for deformable block motion information derivation is proposed, which considers bilinear interpolation model, six-parameter affine model, and four-parameter affine model simultaneously. The sum of absolute transformed differences criterion is used to select the best model for a block. In the proposed merge mode, the motion information of the current block is derived from the motion information of its neighbors. It does not need to perform ME and transmit motion parameters. The proposed merge mode is integrated into HEVC test model (HM) 14.0. The simulation results show that compared with HM14.0, the proposed merge mode can bring 1.3%, 1.7%, and 2.7% Bjontegaard delta (BD) bitrate savings on average for test sequences of HEVC, and 11.0%, 15.2%, and 17.4% BD bitrate savings for deformation sequences in random access main, low-delay B main, and low-delay P main test conditions, respectively, while the increased encoding and decoding complexities are moderate.

Restricted affine motion compensation and estimation in video coding with particle filtering and importance sampling: a multi-resolution approach

In this paper, we propose a multi-resolution affine block-based tracker for motion estimation and compensation, compatible with existing video coding standards such as H.264 and HEVC. We propose three modifications to traditional motion compensation techniques in video coding standards such as H.264 and HEVC. First, we replace traditional search methods with an efficient particle filtering-based method, which incorporates information from both spatial and temporal continuity. Second, we use a higher order linear model in place of the traditional translation motion model in these standards to efficiently represent complex motions such as rotation and zoom. Third, we propose a multi-resolution framework that enables efficient parameter estimation. Results of extensive experimentation show reduced residual energy and better Peak Signal-to-Noise Ratio (PSNR, hereafter) as compared to H.264/HEVC for instance, especially in regions of complex motion such as zooming and rotation.

バックステッピング法と最適サーボ系の組み合わせによるシングルロータヘリの高速旋回飛行制御系の設計とその実験的検証

Aiming at the realization of agile autonomous flight for the extension of the flying range of single-rotor helicopters in the limited flight time, the flight control system design and the control performance verification for the high-speed turn flight are conducted. To achieve the reference following control for large attitude angles and the rotor thrust, the control system is composed of the main-rotor thrust and body torque centralized controller based on the MIMO (Multiple-Input, Multiple-Output) helicopter model including the blade motion dynamics, rotor speed proportional-integral controller, the attitude controller designed via the backstepping method based on the quaternion attitude model, and the guidance controller based on translational motion model. Simulation results show that the hovering and 10-m/s straight cruise flight followed by over 45-degree bank turn is feasible by using the proposed control system. In addition, flight tests have been conducted using the experimental small unmanned electric helicopter equipped with the flight control computer, and the high speed turn agile autonomous flight was successful in the real environment.