In dynamic scenes,the pose estimation and map consistency of visual simultaneous localisation and mapping(visual SLAM)are affected by intermittent changes in object motion states.An adaptive motion-state estimation an...In dynamic scenes,the pose estimation and map consistency of visual simultaneous localisation and mapping(visual SLAM)are affected by intermittent changes in object motion states.An adaptive motion-state estimation and feature-reuse mechanism is proposed which restores features once objects become stationary.Camera ego-motion is com-pensated via projection-based point-to-point red-green-blue-depth(RGB-D)Iterative Closest Point;the alignment residual yields a short-term jitter score.An Extended Kalman Filter fuses the centre-pixel trajectory and depth of the object,using depth innovation as strong evidence to suppress false triggers.Applied adaptive decision thresholds involve resolution,ego-motion intensity,jitter,and reference depth,and are combined with dual/single triggering and hysteresis to achieve robust switching.When an object is considered static,its feature points are reused.On the Bonn RGB-D Dynamic Dataset(BONN)and TUM RGB-D SLAM Dataset and Benchmark(TUM),the proposed method matches or exceeds baselines:In intermittent-motion-dominated BONN sequences Placing_non_box,it re-duces the root-mean-square of the absolute trajectory error(ATE-RMSE)by 27%relative to the baseline,remains comparable to Ellipsoid-SLAM on TUM,and consistently outperforms ORB-SLAM3 in dynamic scenes.The hysteresis counter reading on Placing_non_box2 shows that the proposed method can reduce the motion-state misclassification rate by nearly 40%.From the ablation experiment results,we confirm that adaptive thresholds yield the most significant optimisation effect.The approach improves robustness and map completeness in dynamic environments without degrading performance in low-dynamic settings.展开更多
The side information quality has an immense effect on the compression efficiency of the distributed video coding (DVC) sys- tem. This article, based on the hierarchical motion estimation (HME), proposes a new side inf...The side information quality has an immense effect on the compression efficiency of the distributed video coding (DVC) sys- tem. This article, based on the hierarchical motion estimation (HME), proposes a new side information generation algorithm which is integrated into DVC system. First, forward motion estimation (FME) and bidirectional motion estimation (BME) on the basis of variable block size HME algorithm are used to acquire relatively accurate motion vectors. Second, a motion vector filter (MVF) is i...展开更多
An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algor...An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.展开更多
A novel and effective approach to global motion estimation and moving object extraction is proposed. First, the translational motion model is used because of the fact that complex motion can be decomposed as a sum of ...A novel and effective approach to global motion estimation and moving object extraction is proposed. First, the translational motion model is used because of the fact that complex motion can be decomposed as a sum of translational components. Then in this application, the edge gray horizontal and vertical projections are used as the block matching feature for the motion vectors estimation. The proposed algorithm reduces the motion estimation computations by calculating the onedimensional vectors rather than the two-dimensional ones. Once the global motion is robustly estimated, relatively stationary background can be almost completely eliminated through the inter-frame difference method. To achieve an accurate object extraction result, the higher-order statistics （HOS） algorithm is used to discriminate backgrounds and moving objects. Experimental results validate that the proposed method is an effective way for global motion estimation and object extraction.展开更多
A new motion model and estimation algorithm is proposed to compute the general rigid motion object＇s 6-DOF motion parameters and center of rotation based on stereo vision. The object＇s 6-DOF motion model is designed...A new motion model and estimation algorithm is proposed to compute the general rigid motion object＇s 6-DOF motion parameters and center of rotation based on stereo vision. The object＇s 6-DOF motion model is designed from the rigid object＇s motion character under the two defined reference frames. According to the rigid object＇s motion model and motion dynamics knowledge, the corresponding motion algorithm to compute the 6-DOF motion parameters is worked out. By the rigid object pure rotation motion model and space sphere geometry knowledge, the center of rotation may be calculated after eliminating the translation motion out of the 6-DOF motion. The motion equations are educed based on the motion model and the closed-form solutions are figured out. To heighten the motion estimation algorithm＇s robust, RANSAC algorithm is applied to delete the outliers. Simulation and real experiments are conducted and the experiment results are analyzed. The results prove the motion model＇s correction and algorithm＇s validity.展开更多
Phase errors in synthetic aperture sonar (SAS) imaging must be reduced to less than one eighth of a wavelength so as to avoid image destruction. Most of the phase errors occur as a result of platform motion errors, fo...Phase errors in synthetic aperture sonar (SAS) imaging must be reduced to less than one eighth of a wavelength so as to avoid image destruction. Most of the phase errors occur as a result of platform motion errors, for example, sway yaw and surge that are the most important error sources. The phase error of a wide band synthetic aperture sonar is modeled and solutions to sway yaw and surge motion estimation based on the raw sonar echo data with a Displaced Phase Center Antenna (DPCA) method are proposed and their implementations are detailed in this paper. It is shown that the sway estimates can be obtained from the correlation lag and phase difference between the returns at coincident phase centers. An estimate of yaw is also possible if such a technique is applied to more than one overlapping phase center positions. Surge estimates can be obtained by identifying pairs of phase centers with a maximum correlation coefficient. The method works only if the platform velocity is low enough such that a number of phase centers from adjacent pings overlap.展开更多
Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the air...Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the aircraft motion information, but the six-(degree of freedom)(6-DOF) motion still couldn't be accurately estimated by existing methods. The purpose of this work is to provide a motion estimation method based on optical flow from forward and down looking cameras, which doesn't rely on the assumption of level flight. First, the distribution and decoupling method of optical flow from forward camera are utilized to get attitude. Then, the resulted angular velocities are utilized to obtain the translational optical flow of the down camera, which can eliminate the influence of rotational motion on velocity estimation. Besides, the translational motion estimation equation is simplified by establishing the relation between the depths of feature points and the aircraft altitude. Finally, simulation results show that the method presented is accurate and robust.展开更多
Vision localization methods have been widely used in the motion estimation of unmanned aerial vehicles(UAVs).The noise of the vision location result is usually modeled as a white Gaussian noise so that this location r...Vision localization methods have been widely used in the motion estimation of unmanned aerial vehicles(UAVs).The noise of the vision location result is usually modeled as a white Gaussian noise so that this location result could be utilized as the observation vector in the Kalman filter to estimate the motion of the vehicle.Since the noise of the vision location result is affected by external environment,the variance of the noise is uncertain.However,in previous researches,the variance is usually set as a fixed empirical value,which will lower the accuracy of the motion estimation.The main contribution of this paper is that we proposed a novel adaptive noise variance identification(ANVI) method,which utilizes the special kinematic properties of the UAV for frequency analysis and then adaptively identifies the variance of the noise.The adaptively identified variance is used in the Kalman filter for more accurate motion estimation.The performance of the proposed method is assessed by simulations and field experiments on a quadrotor system.The results illustrate the effectiveness of the method.展开更多
In this article, we study a least squares estimator （LSE） of θ for the Ornstein- Uhlenbeck process X0=0,dXt=θXtdt＋dBt^ab, t ≥ 0 driven by weighted fractional Brownian motion B^a,b with parameters a, b. We obtain...In this article, we study a least squares estimator （LSE） of θ for the Ornstein- Uhlenbeck process X0=0,dXt=θXtdt＋dBt^ab, t ≥ 0 driven by weighted fractional Brownian motion B^a,b with parameters a, b. We obtain the consistency and the asymptotic distribution of the LSE based on the observation {Xs, s∈[0,t]} as t tends to infinity.展开更多
The limitation of processing power, battery life and memory capacity of portable terminals requires reducing encoding complexity in mobile communications. Motion estimation (ME) is the most computationally intensive m...The limitation of processing power, battery life and memory capacity of portable terminals requires reducing encoding complexity in mobile communications. Motion estimation (ME) is the most computationally intensive module in a typical video codec, which determines not only the encoder's performance but also the reconstructed video quality. In this paper, a fast ME algorithm for H.264/AVC baseline profile coding is proposed based on the analysis of motion vector field and error surface, and the statistical distributions of different type macroblocks (MBs). Simulation results showed that: in comparison with MVFAST,the proposed algorithm can decrease the computational load over 7.2% with no requirement of expanding memory capacity while maintaining the same video quality as MVFAST. Furthermore, its simplicity makes it easy to be implemented on hardware.展开更多
Aiming at the higher bit-rate occupation of motion vector encoding and more time load of full-searching strategies, a multi-resolution motion estimation and compensation algorithm based on adjacent prediction of frame...Aiming at the higher bit-rate occupation of motion vector encoding and more time load of full-searching strategies, a multi-resolution motion estimation and compensation algorithm based on adjacent prediction of frame difference was proposed.Differential motion detection was employed to image sequences and proper threshold was adopted to identify the connected region.Then the motion region was extracted to carry out motion estimation and motion compensation on it.The experiment results show that the encoding efficiency of motion vector is promoted, the complexity of motion estimation is reduced and the quality of the reconstruction image at the same bit-rate as Multi-Resolution Motion Estimation(MRME) is improved.展开更多
A correlation tracking algorithm based on template partition motion estimation proposed for improving real time performance of the conventional correlation matching algorithms. The target trajectory fitted using the l...A correlation tracking algorithm based on template partition motion estimation proposed for improving real time performance of the conventional correlation matching algorithms. The target trajectory fitted using the least square with equal space in whole interval and the target prediction point is found out. According to the requirements of block motion estimation(BME) algorithm,the template divided into some macro blocks. The searching process is conducted by using diamond search algorithm around the prediction point and the optimal motion vector of each block is calculated. A point corresponding to the motion vector with the best matching is taken as a rough matching point of the template. The relation of relative position between the block with matching point and the searching area determined to decide whether to conduct precise matching search or to construct a new search area in the gradient direction. The target tracking experiment results show that over 70% time cost can be reduced caompared with the conventional correlation matching algorithm based on full search method.展开更多
In this paper,we propose a novel adjustable multiple cross-hexagonal search(AMCHS) algorithm for fast block motion estimation. It employs adjustable multiple cross search patterns(AMCSP) in the first step and then use...In this paper,we propose a novel adjustable multiple cross-hexagonal search(AMCHS) algorithm for fast block motion estimation. It employs adjustable multiple cross search patterns(AMCSP) in the first step and then uses half-way-skip and half-way-stop technique to determine whether to employ two hexagonal search patterns(HSPs) subsequently. The AMCSP can be used to find small motion vectors efficiently while the HSPs can be used to find large ones accurately to ensure prediction quality. Simulation results showed that our proposed AMCHS achieves faster search speed,and provides better distortion performance than other popular fast search algorithms,such as CDS and CDHS.展开更多
H.264/AVC video coding standard can achieve roughly half of the bit-savings over MPEG2 and MPEG4 for a given quality.However,this comes at a cost in considerably increased complexity at the encoder and thus increases ...H.264/AVC video coding standard can achieve roughly half of the bit-savings over MPEG2 and MPEG4 for a given quality.However,this comes at a cost in considerably increased complexity at the encoder and thus increases the difficulty in hardware implementation.The high redundancy that exists between the successive frames of a video sequence makes it possible to achieve a high data compression ratio.Motion estimation(ME)plays an important role in motion compensated video coding.A fast motion estimation algorithm for H.264/AVC is proposed based on centered prediction,called centered prediction based fast mixed search algorithm(CPFMS).It makes use of the spatial and temporal correlation in motion vector(MV)fields and feature of all-zero blocks to accelerate the searching process.With the initialized searching point prediction,adaptive search window changing and searching direction decision,CPFMS is provided to reduce computation in block-matching process.The experimental results show that the speed of CPFMS is nearly 12 times of FS with a negligible peak signal-noise ratio(PSNR)loss.Also,the efficiency of CPFMS outperforms some popular fast algorithms such as hybrid unsymmetrical cross multi-hexagongrid search and a novel multidirectional gradient descent search evidently.展开更多
Single image motion deblurring has been a very challenging problem in the field of image processing. Although there are many researches had been proposed to solve this problem, it still has problems on kernel accuracy...Single image motion deblurring has been a very challenging problem in the field of image processing. Although there are many researches had been proposed to solve this problem, it still has problems on kernel accuracy. In order to improve the kernel accuracy, an effective structure selection method was used to select the salient structure of the blur image. Then a novel kernel estimation method based on L0-2 norm was proposed. To guarantee the sparse kernel and eliminate the negative influence of details L0-norm was used. And L2-norm was used to ensure the continuity of kernel. Many experiments were done to compare proposed method and state-of-the-art methods. The results show that our method can estimate a better kernel and use less time than previous work, especially when the size of blur kernel is large.展开更多
In this paper, a Modified Complex Lapped Transform domain Motion Estimation (MCLT-ME) method to estimate the motion of video sequence is proposed. The proposed method is based on phase correlation of current window re...In this paper, a Modified Complex Lapped Transform domain Motion Estimation (MCLT-ME) method to estimate the motion of video sequence is proposed. The proposed method is based on phase correlation of current window region and corresponding window region, and provides a significant improvement in motion estimation.展开更多
Determination of relative three-dimensional （3D） position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fi...Determination of relative three-dimensional （3D） position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry. A solution to pose and motion estimation problem that uses two-dimensional （2D） intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter （GPF） based on the panicle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter （EKF） and the unscented Kalman filter （UKF） to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.展开更多
文摘In dynamic scenes,the pose estimation and map consistency of visual simultaneous localisation and mapping(visual SLAM)are affected by intermittent changes in object motion states.An adaptive motion-state estimation and feature-reuse mechanism is proposed which restores features once objects become stationary.Camera ego-motion is com-pensated via projection-based point-to-point red-green-blue-depth(RGB-D)Iterative Closest Point;the alignment residual yields a short-term jitter score.An Extended Kalman Filter fuses the centre-pixel trajectory and depth of the object,using depth innovation as strong evidence to suppress false triggers.Applied adaptive decision thresholds involve resolution,ego-motion intensity,jitter,and reference depth,and are combined with dual/single triggering and hysteresis to achieve robust switching.When an object is considered static,its feature points are reused.On the Bonn RGB-D Dynamic Dataset(BONN)and TUM RGB-D SLAM Dataset and Benchmark(TUM),the proposed method matches or exceeds baselines:In intermittent-motion-dominated BONN sequences Placing_non_box,it re-duces the root-mean-square of the absolute trajectory error(ATE-RMSE)by 27%relative to the baseline,remains comparable to Ellipsoid-SLAM on TUM,and consistently outperforms ORB-SLAM3 in dynamic scenes.The hysteresis counter reading on Placing_non_box2 shows that the proposed method can reduce the motion-state misclassification rate by nearly 40%.From the ablation experiment results,we confirm that adaptive thresholds yield the most significant optimisation effect.The approach improves robustness and map completeness in dynamic environments without degrading performance in low-dynamic settings.
基金National Natural Science Foundation of China (60702012)
文摘The side information quality has an immense effect on the compression efficiency of the distributed video coding (DVC) sys- tem. This article, based on the hierarchical motion estimation (HME), proposes a new side information generation algorithm which is integrated into DVC system. First, forward motion estimation (FME) and bidirectional motion estimation (BME) on the basis of variable block size HME algorithm are used to acquire relatively accurate motion vectors. Second, a motion vector filter (MVF) is i...
文摘An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.
基金The National Natural Science Foundation of China(No.60574006)
文摘A novel and effective approach to global motion estimation and moving object extraction is proposed. First, the translational motion model is used because of the fact that complex motion can be decomposed as a sum of translational components. Then in this application, the edge gray horizontal and vertical projections are used as the block matching feature for the motion vectors estimation. The proposed algorithm reduces the motion estimation computations by calculating the onedimensional vectors rather than the two-dimensional ones. Once the global motion is robustly estimated, relatively stationary background can be almost completely eliminated through the inter-frame difference method. To achieve an accurate object extraction result, the higher-order statistics （HOS） algorithm is used to discriminate backgrounds and moving objects. Experimental results validate that the proposed method is an effective way for global motion estimation and object extraction.
基金National Natural Science Foundation of China (No.50275040)
文摘A new motion model and estimation algorithm is proposed to compute the general rigid motion object＇s 6-DOF motion parameters and center of rotation based on stereo vision. The object＇s 6-DOF motion model is designed from the rigid object＇s motion character under the two defined reference frames. According to the rigid object＇s motion model and motion dynamics knowledge, the corresponding motion algorithm to compute the 6-DOF motion parameters is worked out. By the rigid object pure rotation motion model and space sphere geometry knowledge, the center of rotation may be calculated after eliminating the translation motion out of the 6-DOF motion. The motion equations are educed based on the motion model and the closed-form solutions are figured out. To heighten the motion estimation algorithm＇s robust, RANSAC algorithm is applied to delete the outliers. Simulation and real experiments are conducted and the experiment results are analyzed. The results prove the motion model＇s correction and algorithm＇s validity.
文摘Phase errors in synthetic aperture sonar (SAS) imaging must be reduced to less than one eighth of a wavelength so as to avoid image destruction. Most of the phase errors occur as a result of platform motion errors, for example, sway yaw and surge that are the most important error sources. The phase error of a wide band synthetic aperture sonar is modeled and solutions to sway yaw and surge motion estimation based on the raw sonar echo data with a Displaced Phase Center Antenna (DPCA) method are proposed and their implementations are detailed in this paper. It is shown that the sway estimates can be obtained from the correlation lag and phase difference between the returns at coincident phase centers. An estimate of yaw is also possible if such a technique is applied to more than one overlapping phase center positions. Surge estimates can be obtained by identifying pairs of phase centers with a maximum correlation coefficient. The method works only if the platform velocity is low enough such that a number of phase centers from adjacent pings overlap.
基金Project(2012CB720003)supported by the National Basic Research Program of ChinaProjects(61320106010,61127007,61121003,61573019)supported by the National Natural Science Foundation of ChinaProject(2013DFE13040)supported by the Special Program for International Science and Technology Cooperation from Ministry of Science and Technology of China
文摘Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the aircraft motion information, but the six-(degree of freedom)(6-DOF) motion still couldn't be accurately estimated by existing methods. The purpose of this work is to provide a motion estimation method based on optical flow from forward and down looking cameras, which doesn't rely on the assumption of level flight. First, the distribution and decoupling method of optical flow from forward camera are utilized to get attitude. Then, the resulted angular velocities are utilized to obtain the translational optical flow of the down camera, which can eliminate the influence of rotational motion on velocity estimation. Besides, the translational motion estimation equation is simplified by establishing the relation between the depths of feature points and the aircraft altitude. Finally, simulation results show that the method presented is accurate and robust.
基金supported by National Science and Technology Major Projects of the Ministry of Science and Technology of China:ITER(No.2012GB102007)
文摘Vision localization methods have been widely used in the motion estimation of unmanned aerial vehicles(UAVs).The noise of the vision location result is usually modeled as a white Gaussian noise so that this location result could be utilized as the observation vector in the Kalman filter to estimate the motion of the vehicle.Since the noise of the vision location result is affected by external environment,the variance of the noise is uncertain.However,in previous researches,the variance is usually set as a fixed empirical value,which will lower the accuracy of the motion estimation.The main contribution of this paper is that we proposed a novel adaptive noise variance identification(ANVI) method,which utilizes the special kinematic properties of the UAV for frequency analysis and then adaptively identifies the variance of the noise.The adaptively identified variance is used in the Kalman filter for more accurate motion estimation.The performance of the proposed method is assessed by simulations and field experiments on a quadrotor system.The results illustrate the effectiveness of the method.
基金supported by the National Natural Science Foundation of China(11271020)the Distinguished Young Scholars Foundation of Anhui Province(1608085J06)supported by the National Natural Science Foundation of China(11171062)
文摘In this article, we study a least squares estimator （LSE） of θ for the Ornstein- Uhlenbeck process X0=0,dXt=θXtdt＋dBt^ab, t ≥ 0 driven by weighted fractional Brownian motion B^a,b with parameters a, b. We obtain the consistency and the asymptotic distribution of the LSE based on the observation {Xs, s∈[0,t]} as t tends to infinity.
文摘The limitation of processing power, battery life and memory capacity of portable terminals requires reducing encoding complexity in mobile communications. Motion estimation (ME) is the most computationally intensive module in a typical video codec, which determines not only the encoder's performance but also the reconstructed video quality. In this paper, a fast ME algorithm for H.264/AVC baseline profile coding is proposed based on the analysis of motion vector field and error surface, and the statistical distributions of different type macroblocks (MBs). Simulation results showed that: in comparison with MVFAST,the proposed algorithm can decrease the computational load over 7.2% with no requirement of expanding memory capacity while maintaining the same video quality as MVFAST. Furthermore, its simplicity makes it easy to be implemented on hardware.
基金Supported by the National Natural Science Foundation of China (No. 60803036)the Scientific Research Fund of Heilongjiang Provincial Education Department (No.11531013)
文摘Aiming at the higher bit-rate occupation of motion vector encoding and more time load of full-searching strategies, a multi-resolution motion estimation and compensation algorithm based on adjacent prediction of frame difference was proposed.Differential motion detection was employed to image sequences and proper threshold was adopted to identify the connected region.Then the motion region was extracted to carry out motion estimation and motion compensation on it.The experiment results show that the encoding efficiency of motion vector is promoted, the complexity of motion estimation is reduced and the quality of the reconstruction image at the same bit-rate as Multi-Resolution Motion Estimation(MRME) is improved.
基金Sponsored by the National Defense Pre-Research Foundation of China
文摘A correlation tracking algorithm based on template partition motion estimation proposed for improving real time performance of the conventional correlation matching algorithms. The target trajectory fitted using the least square with equal space in whole interval and the target prediction point is found out. According to the requirements of block motion estimation(BME) algorithm,the template divided into some macro blocks. The searching process is conducted by using diamond search algorithm around the prediction point and the optimal motion vector of each block is calculated. A point corresponding to the motion vector with the best matching is taken as a rough matching point of the template. The relation of relative position between the block with matching point and the searching area determined to decide whether to conduct precise matching search or to construct a new search area in the gradient direction. The target tracking experiment results show that over 70% time cost can be reduced caompared with the conventional correlation matching algorithm based on full search method.
文摘In this paper,we propose a novel adjustable multiple cross-hexagonal search(AMCHS) algorithm for fast block motion estimation. It employs adjustable multiple cross search patterns(AMCSP) in the first step and then uses half-way-skip and half-way-stop technique to determine whether to employ two hexagonal search patterns(HSPs) subsequently. The AMCSP can be used to find small motion vectors efficiently while the HSPs can be used to find large ones accurately to ensure prediction quality. Simulation results showed that our proposed AMCHS achieves faster search speed,and provides better distortion performance than other popular fast search algorithms,such as CDS and CDHS.
基金supported by the National Natural Science Foundation of China(60902101)Fundmental Research Foundation of North-western Polytechnical University(JC200913)
文摘H.264/AVC video coding standard can achieve roughly half of the bit-savings over MPEG2 and MPEG4 for a given quality.However,this comes at a cost in considerably increased complexity at the encoder and thus increases the difficulty in hardware implementation.The high redundancy that exists between the successive frames of a video sequence makes it possible to achieve a high data compression ratio.Motion estimation(ME)plays an important role in motion compensated video coding.A fast motion estimation algorithm for H.264/AVC is proposed based on centered prediction,called centered prediction based fast mixed search algorithm(CPFMS).It makes use of the spatial and temporal correlation in motion vector(MV)fields and feature of all-zero blocks to accelerate the searching process.With the initialized searching point prediction,adaptive search window changing and searching direction decision,CPFMS is provided to reduce computation in block-matching process.The experimental results show that the speed of CPFMS is nearly 12 times of FS with a negligible peak signal-noise ratio(PSNR)loss.Also,the efficiency of CPFMS outperforms some popular fast algorithms such as hybrid unsymmetrical cross multi-hexagongrid search and a novel multidirectional gradient descent search evidently.
文摘Single image motion deblurring has been a very challenging problem in the field of image processing. Although there are many researches had been proposed to solve this problem, it still has problems on kernel accuracy. In order to improve the kernel accuracy, an effective structure selection method was used to select the salient structure of the blur image. Then a novel kernel estimation method based on L0-2 norm was proposed. To guarantee the sparse kernel and eliminate the negative influence of details L0-norm was used. And L2-norm was used to ensure the continuity of kernel. Many experiments were done to compare proposed method and state-of-the-art methods. The results show that our method can estimate a better kernel and use less time than previous work, especially when the size of blur kernel is large.
文摘In this paper, a Modified Complex Lapped Transform domain Motion Estimation (MCLT-ME) method to estimate the motion of video sequence is proposed. The proposed method is based on phase correlation of current window region and corresponding window region, and provides a significant improvement in motion estimation.
基金Project (No. 2006J0017) supported by the Natural Science Foundation of Fujian Province, China
文摘Determination of relative three-dimensional （3D） position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry. A solution to pose and motion estimation problem that uses two-dimensional （2D） intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter （GPF） based on the panicle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter （EKF） and the unscented Kalman filter （UKF） to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.
