Motion Vectors Of Objects Research Articles

A Novel Gaming Video Encoding Process Using In-Game Motion Vectors

In this paper, we propose a motion preprocessing method for the use in the game application pipeline, which is composed of two stages: the proposed preprocessing method and the High Efficiency Video Coding (HEVC) encoder. The method accepts the object information from the game application, preprocesses the motion vectors of objects, and pass the preprocessed motion data to the HEVC encoder. The HEVC encoder takes the motion data as the initial (or the dedicated) value of motion estimation. Therefore, the traditional diamond search can be skipped and hence increase the encoding performance of the HEVC encoder. In the motion preprocessing method, the following three steps are taken: a coordination system transformation, determining motion vectors for $4\times 4$ -checkerboard blocks [Atomic Block (AB)], and the selection of proper motion vectors for all varieties of prediction units in the encoder. With a focus on the special issues, such as move-out zone and bi-directional prediction, we are able to further optimize the performance of the encoder. We examined two types of 2D gaming scenes in our experiments. The experimental results show that, as compared with the original diamond search method provided by the encoder, our algorithm is able to achieve up to 49.0% time reduction of video encoding. The Bjontegaard Delta bit rate can achieve up to −17.0% in the random_access mode while combining with the $\times 265$ encoder and up to −26.2% in the lowdelay mode while combining with the HM-16 encoder.

집적영상에서 효율적인 물체움직임 추정 및 차 영상 기법을 이용한 서브영상의 고속 압축

In this paper, we propose a novel approach to effectively compress the sub-images transformed from the picked-up elemental images in integral imaging, in which motion vectors of the object in each sub-image are fast and accurately estimated and compensated by combined use of MSE(mean square error)-based TSS(tree-step search) and FS(full search) schemes. This is, the possible object areas in each sub-image are searched by using the fast TSS algorithm in advance, then the these selected object areas are fully searched with the accurate FS algorithm. Furthermore, the sub-images in which all object's motion vectors are compensated, are transformed into the residual images by using the difference image method and finally compressed with the MPEG-4 algorithm. Experimental results reveal that the proposed method shows 214% improvement in the compression time per each image frame compared to that of the conventional method while keeping the same compression ratio with the conventional method. These successful results confirm the feasibility of the proposed method in the practical application.

Motion Analysis Using 3D High-Resolution Frequency Analysis

The spatiotemporal spectra of a video that contains a moving object form a plane in the 3D frequency domain. This plane, which is described as the theoretical motion plane, reflects the velocity of the moving objects, which is calculated from the slope. However, if the resolution of the frequency analysis method is not high enough to obtain actual spectra from the object signal, the spatiotemporal spectra disperse away from the theoretical motion plane. In this paper, we propose a high-resolution frequency analysis method, described as 3D nonharmonic analysis (NHA), which is only weakly influenced by the analysis window. In addition, we estimate the motion vectors of objects in a video using the plane-clustering method, in conjunction with the least-squares method, for 3D NHA spatiotemporal spectra. We experimentally verify the accuracy of the 3D NHA and its usefulness for a sequence containing complex motions, such as cross-over motion, through comparison with 3D fast Fourier transform. The experimental results show that increasing the frequency resolution contributes to high-accuracy estimation of a motion plane.

A debris image tracking using optical flow algorithm

This study proposes a motion detection and object tracking technique for GEO debris in a sequence of images. A couple of techniques (called the “stacking method” and “line-identifying technique”) were recently proposed to address the same problem. Although these techniques are effective at detecting the debris position and motion in the image sequences, there are some issues concerned with computational load and assumed debris motion. This study derives a method to estimate motion vectors of objects in image sequence and finally detect the debris locations by using a computer vision technique called an optical flow algorithm. The new method detects these parameters in low computational time in a serial manner, which implies that it has an advantage to track not only linear but also nonlinear motion of GEO debris more easily than the previous methods. The feasibility of the proposed methods is validated using real and synthesized image sequences which contain some typical debris motions.

주문형 게임 서비스를 위한 장면 기술자 기반 고속 게임 부호화기

주문형 게임 서비스는 서버에서 실행하는 게임을 동영상 부호화하여 클라이언트에 전송하고, 클라이언트에서 비디오 복호화를 통해 게임을 즐길 수 있게 해 준다. 다수의 사용자가 네트워크상에서 실시간 게임 서비스를 즐기기 위해서는 초고속 게임 인코더가 필요하다. 본 논문에서 제안한 방법은 장면 기술자를 정의하고, 이를 게임 영상을 부호화하는 부호화기에 부가적인 정보로 입력함으로써 움직임 예측, 율 왜곡 최적화와 같은 복잡도가 높은 부호화 과정을 생략하여 부호화기를 고속화한다. 장면 기술자를 움직임 벡터로 사용하고, 장면 기술자를 이용하여 매크로블록 모드를 결정해 부호화기를 고속화한다. 제안하는 방법의 성능 평가를 위해 H.264/AVC의 오픈 소프트웨어인 x264와 비교한 결과, x264에 어셈블리 코드가 포함되지 않은 경우에 대해서 약 192%의 부호화 속도 향상을 확인하였고, x264에서 일부 모듈에 대해서 어셈블리 최적화를 반영한 결과에 대해서는 86%의 부호화 속도가 향상되는 것을 확인할 수 있었다. 부호화기의 고속화 결과 60 FPS의 부호화 속도를 넘어 주문형 게임을 실시간으로 수행할 수 있게 되었다. Gaming on demand(GOD) makes people enjoy games by encoding and transmitting game screen at a server side, and decoding the video at a client side. In this paper, we propose a fast game video encoder for multiple users over network with low-powered devices. In the proposed system, the computational complexity of game encoders is reduced by using scene descriptors, which consists of an object motion vector, global motion, and scene change. With additional information from game engines, the proposed encoder does not need to perform various complexity processes such as motion estimation and ratedistortion optimization. The motion estimation and rate-distortion optimization skipped by scene descriptors. We found that the proposed method improved 192 % in terms of FPS, compared with x264 software. With partial assembly code, we also improved coding speed by 86 % in terms of FPS. We found that the proposed fast encoder could encode over 60 FPS for real-time GOD applications.

Multiresolution segmentation of video objects in the compression domain

This paper proposes a multiresolution method for video object segmentation in the compression domain. We first calculate global motion parameters using only background macroblocks with tiny residual dc coefficients of the P frame, and then get true motion vectors projected to the immediate adjoined I frame. The basic layer image is obtained with only dc coefficients of the I frame. The enhancement texture characteristics are provided by the ac coefficients for partial decoding. The true object motion vectors and the basic layer image are fed into a morphological motion filter to get the lowest-resolution regions of moving objects, called the layer4 region of interest (L4-ROI). Only some of the ac coefficients in L4-ROI are decoded to obtain a higher-resolution image, called layer3, that mainly consists of blocks of the moving object. The moving object of interest in the highest resolution is obtained from a morphological motion filter with L2-ROI and the true object motion vectors. The number of ac coefficients determines the resulting resolution. Experiments show that the new algorithm can extract multiresolution moving objects efficiently.

Filtering of Block Motion Vectors for Use in Motion-Based Video Indexing and Retrieval

Though block-based motion estimation techniques are primarily designed for video coding applications, they are increasingly being used in other video analysis applications due to their simplicity and ease of implementation. The major drawback associated with these techniques is that noises, in the form of false motion vectors, cannot be avoided while capturing block motion vectors. Similar noises may further be introduced when the technique of global motion compensation is applied to obtain true object motion from video sequences where both the camera and object motions are present. This paper presents a new technique for capturing large number of true object motion vectors by eliminating the false motion vector fields, for use in the application of object motion based video indexing and retrieval applications. Experimental results prove that our proposed technique significantly increases the percentage of retained true object motion vectors while eliminating all false motion vectors for variety of standard and non-standard video sequences.

Shape coding using temporal correlation and joint VLC optimization

This paper investigates ways to explore the between frame correlation of shape information within the framework of an operationally rate-distortion (ORD) optimized coder. Contours are approximated both by connected second-order spline segments, each defined by three consecutive control points, and by segments of the motion-compensated reference contours. Consecutive control points are then encoded predictively using angle and run temporal contexts or by tracking the reference contour. We utilize a novel criterion for selecting global object motion vectors, which improves the efficiency. The problem is formulated as a Lagrangian minimization and solved using dynamic programming. Furthermore, we employ an iterative technique to remove dependency on a particular variable length code and jointly arrive at the ORD globally optimal solution and an optimized conditional parameter distribution.