Motion Vector Map Research Articles

Jomodevi: A joint motion and depth visibility prediction algorithm for perceived stereoscopic 3D quality

In this paper, we introduce a completely blind and unsupervised no-reference model that performs the quality assessment of stereoscopic 3D videos by using joint motion and depth visibility. In order to achieve such objective metric, first we compute the correlation map between the motion vector map and the depth map, and then we study the natural scene statistics of the estimated correlation map. We empirically model these statistics with Univariate Generalized Gaussian Distribution (UGGD) and compute the UGGD parameters at multi-scale and multi-orient steerable subband decomposition. It is shown that the estimated UGGD features are capable of discriminating distortions. We then compute the mean vector and the covariance matrix from the estimated UGGD features of the correlation maps of motion vector and the depth maps of undistorted and distorted S3D videos. This is followed by the computation of the Wave Hedges distance between the mean vectors of the undistorted and distorted contents, and the Bhattacharyya distance is measured between the corresponding covariance matrices. We pool these distance measures to achieve the overall joint motion and depth quality of S3D videos. The efficiency of the proposed algorithm is evaluated on the well-known IRCCYN, LFOVIAS3DPh1 and LFOVIAS3DPh2 S3D video datasets. Our model demonstrates robust and consistent performance across all distortion types and shows competitive performance against other 2D and 3D image and video quality assessment algorithms. Furthermore, since the proposed algorithm is completely blind, it does not require any training and testing analysis on the content features and the subjective scores.

3D lung motion assessments on inspiratory/expiratory thin-section CT: Capability for pulmonary functional loss of smoking-related COPD in comparison with lung destruction and air trapping

PurposeTo evaluate the utility of three-dimensional (3D) lung motion on inspiratory and expiratory CT for pulmonary functional loss in smoking-related COPD in comparison with lung destruction and air trapping assessments. Method and materialsForty-four consecutive smokers and COPD patients prospectively underwent inspiratory and expiratory CT. A 3D motion vector map was generated from these CTs, and regional motion magnitudes were measured at the horizontal axis (X-axis), the ventrodorsal axis (Y-axis), and the craniocaudal axis (Z-axis). All mean magnitudes within the entire lung (MMLX, MMLY, and MMLZ) were normalized by expiratory CT lung volume. Moreover, CT-based functional lung volume (FLV) on inspiratory CT and air trapping lung volume (ATLV) on expiratory CT were assessed quantitatively. To evaluate the capability for pulmonary function loss assessment, all MMLs were correlated with pulmonary function tests. Then, discrimination analysis was performed to determine the concordance capability for clinical stage, and correct classification capabilities were compared by means of McNemar’s test. ResultsMultiple regression analysis showed MMLY (β=0.657, p<0.001) and FLV (β=0.375, p=0.019) were correlated with percentage of predicted forced expiratory volume in 1 second. Correct classification capabilities using patient characteristics and MMLs (68.2 (30/44)%) were significantly higher than those obtained by patient characteristics, FLV, and ATLV (54.5 (24/44)%), p=0.031). Conclusion3D lung motion parameter assessment is useful for smoking-related COPD assessment as well as lung parenchymal destruction and/or air trapping evaluations.

Bidirectional Mesh-Based Frame Rate Up-Conversion

The authors propose a new frame rate up-conversion (FRUC) method for temporal video quality enhancement. To cope with translation as well as scale and rotation changes, the algorithm generates an interpolated frame between two given frames on the basis of bidirectional mesh interpolation (BMI). BMI performance is highly influenced by the accuracy of the correspondences between the control points in the two frames. To achieve an accurate, dense motion vector map (MVM) through bidirectional and unidirectional motion estimation, the algorithm forms an initial MVM using motion vectors transmitted from the coded bitstream. Then, the algorithm generates the interpolated frame using frame-based BMI with the dense MVM. In experiments, the authors found that the proposed algorithm is about two decibels better than several conventional FRUC methods. Furthermore, the proposed algorithm significantly diminishes block artifacts and blur artifacts.

A Simple and High Performing Rate Control Initialization Method for H.264 AVC Coding Based on Motion Vector Map and Spatial Complexity at Low Bitrate

The temporal complexity of video sequences can be characterized by motion vector map which consists of motion vectors of each macroblock (MB). In order to obtain the optimal initial QP (quantization parameter) for the various video sequences which have different spatial and temporal complexities, this paper proposes a simple and high performance initial QP determining method based on motion vector map and temporal complexity to decide an initial QP in given target bit rate. The proposed algorithm produces the reconstructed video sequences with outstanding and stable quality. For any video sequences, the initial QP can be easily determined from matrices by target bit rate and mapped spatial complexity using proposed mapping method. Experimental results show that the proposed algorithm can show more outstanding objective and subjective performance than other conventional determining methods.

Hybrid Frame Rate Upconversion Method Based on Motion Vector Mapping

Liquid crystal displays (LCDs), which serve as receivers of high visual quality video, suffer from motion blur issues. One of the methods in terminating motion blur is motion compensated frame rate upconversion, which is widely adopted in LCDs. In the previous work, i.e., particle-based frame rate upconversion, the computation complexity is high while repeated operations and some improper cost evaluation setup are observed. Therefore, in this paper, hybrid frame rate upconversion is proposed with two features. First, the cost evaluation for particle-based motion trajectory calibration is modified based on the possible noise sources and video resolution variations. Second, repeated operations in particle-based motion trajectory calibration are observed. Therefore, original particle-based motion trajectory calibration is replaced by initial motion vector assignment and subsequent motion vector mapping to achieve computation complexity reduction, while the effective search range is relatively expanded. According to the experiment results, the visual quality is enhanced by 1.87 dB on average, compared with state-of-the-art unidirectional-based frame rate upconversion approaches. On the other hand, the computation complexity of the proposed design is reduced by 25-90% based on target video resolution, concluding a high visual quality and low computation complexity frame rate upconversion design.

Development of a model of the coronary arterial tree for the 4D XCAT phantom

A detailed three-dimensional (3D) model of the coronary artery tree with cardiac motion has great potential for applications in a wide variety of medical imaging research areas. In this work, we first developed a computer-generated 3D model of the coronary arterial tree for the heart in the extended cardiac-torso (XCAT) phantom, thereby creating a realistic computer model of the human anatomy. The coronary arterial tree model was based on two datasets: (1) a gated cardiac dual-source computed tomography (CT) angiographic dataset obtained from a normal human subject and (2) statistical morphometric data of porcine hearts. The initial proximal segments of the vasculature and the anatomical details of the boundaries of the ventricles were defined by segmenting the CT data. An iterative rule-based generation method was developed and applied to extend the coronary arterial tree beyond the initial proximal segments. The algorithm was governed by three factors: (1) statistical morphometric measurements of the connectivity, lengths and diameters of the arterial segments; (2) avoidance forces from other vessel segments and the boundaries of the myocardium, and (3) optimality principles which minimize the drag force at the bifurcations of the generated tree. Using this algorithm, the 3D computational model of the largest six orders of the coronary arterial tree was generated, which spread across the myocardium of the left and right ventricles. The 3D coronary arterial tree model was then extended to 4D to simulate different cardiac phases by deforming the original 3D model according to the motion vector map of the 4D cardiac model of the XCAT phantom at the corresponding phases. As a result, a detailed and realistic 4D model of the coronary arterial tree was developed for the XCAT phantom by imposing constraints of anatomical and physiological characteristics of the coronary vasculature. This new 4D coronary artery tree model provides a unique simulation tool that can be used in the development and evaluation of instrumentation and methods for imaging normal and pathological hearts with myocardial perfusion defects.

A fast intra mode skip decision algorithm based on adaptive motion vector map

A fast intra mode skip decision algorithm for H.264/AVC video encoding is proposed in this paper. Although the intra macroblock (MB) prediction algorithm, based on various prediction methods based in the pixel domain instead of in the transformed domain, increases the compression ratio, it requires a significant increase in the computational complexity. Although the intra MBs are only a small part of the whole inter frame, large computational loads occur because all MBs must be examined by the intra mode prediction process. To reduce the processing time for the inter frame mode decision, a fast intra mode skip decision scheme is proposed using an adaptive motion vector map (AMVM) algorithm for the H.264/AVC video encoder. It is verified that the proposed algorithm generates generally good performances in PSNR, bit rate, and processing time.

An efficient scheme for motion estimation using multireference frames in H.264/AVC

The multiple reference frame motion compensation (MRMC) supported by H.264 makes use of the redundancy which is between multiple frames to enhance the coding efficiency over a scheme using the single reference frame motion compensation (SRMC) in which motion vectors are searched over a single reference frame. And, the technique using multiple reference frames can combat the channel errors efficiently. However, searching the motion vectors in multiple frames may require a huge computing time. This paper proposes a novel motion estimation procedure, which has a lower search complexity without sacrificing image quality. To reduce the complexity of motion estimation procedure, we use a temporary motion vector generated with little computation. The temporary motion vector is calculated from the motion vector map composed of motion vectors between successive frames, and used to predict the optimal motion vector for a reference frame. The proposed scheme requires the lower complexity than conventional schemes by using the temporary motion vector and refinement process over a narrow search range around the temporary predictive motion vector. Since the temporary predictive motion vector effectively chases the optimal motion vector for each reference frame, the encoded image quality by proposed scheme is very similar to that of full search algorithm. The proposed motion estimation process consists of three phases: 1)making a vector map between two consecutive frames, where the vector map is constructed by copying motion vectors which have been estimated in first reference frame, 2) composing a temporary motion vector with element vectors which are in the vector map, and 3) finally, the temporary predictive motion vector is refined over a narrow search range. We show experimental results which demonstrate the effectiveness of the proposed method. To compare the proposed motion estimation algorithm with the conventional schemes, we check the CPU times consumed by ME module in H.264 encoder using the proposed scheme. In the results, CPU time consumed by the proposed scheme has been reduced significantly without additional distortion of the encoded video quality.

Transactions - Drift compensation for reduced spatial resolution transcoding: a summary

This paper discusses the problem of reduced-resolution transcoding of compressed video bitstreams. An analysis of drift errors is provided to identify the sources of quality degradation when transcoding to a lower spatial resolution. Two types of drift error are considered: a reference picture error, which has been identified in previous works, and error due to the noncommutative property of motion compensation and down-sampling, which is unique to this work. To overcome these sources of error, four novel architectures are presented. One architecture attempts to compensate for the reference picture error in the reduced resolution, while another architecture attempts to do the same in the original resolution. We present a third architecture that attempts to eliminate the second type of drift error and a final architecture that relies on an intrablock refresh method to compensate for all types of errors. In all of these architectures, a variety of macroblock level conversions are required, such as motion vector mapping and texture down-sampling. These conversions are discussed in detail. Another important issue for the transcoder is rate control. This is especially important for the intra-refresh architecture since it must find a balance between number of intrablocks used to compensate for errors and the associated rate-distortion characteristics of the low-resolution signal. The complexity and quality of the architectures are compared. Based on the results, we find that the intra-refresh architecture offers the best tradeoff between quality and complexity and is also the most flexible.

Drift compensation for reduced spatial resolution transcoding

This paper discusses the problem of reduced-resolution transcoding of compressed video bitstreams. An analysis of drift errors is provided to identify the sources of quality degradation when transcoding to a lower spatial resolution. Two types of drift error are considered: a reference picture error, which has been identified in previous works, and error due to the noncommutative property of motion compensation and down-sampling, which is unique to this work. To overcome these sources of error, four novel architectures are presented. One architecture attempts to compensate for the reference picture error in the reduced resolution, while another architecture attempts to do the same in the original resolution. We present a third architecture that attempts to eliminate the second type of drift error and a final architecture that relies on an intrablock refresh method to compensate for all types of errors. In all of these architectures, a variety of macroblock level conversions are required, such as motion vector mapping and texture down-sampling. These conversions are discussed in detail. Another important issue for the transcoder is rate control. This is especially important for the intra-refresh architecture since it must find a balance between number of intrablocks used to compensate for errors and the associated rate-distortion characteristics of the low-resolution signal. The complexity and quality of the architectures are compared. Based on the results, we find that the intra-refresh architecture offers the best tradeoff between quality and complexity and is also the most flexible.