Dissertation > Excellent graduate degree dissertation topics show

Research on Key Technologies of Depth-map Estimation for Free Viewpoint Video

Author: HuoZhiYong
Tutor: ZhuXiuChang
School: Nanjing University of Posts and Telecommunications
Course: Signal and Information Processing
Keywords: Free-viewpoint video Depth maps estimation SFM OFC Regional SteoroMatching DAISY descriptor Epanechnikov weight kernel DIBR
CLC: TP391.41
Type: PhD thesis
Year: 2013
Downloads: 487
Quote: 0
Read: Download Dissertation

Abstract


People can perceive the depth while watching a stereoscopic screen; they can change adifferent viewpoint according to their own preferences while watching multi-view video. It isdifficult to achieve the effects by the ordinary two-dimensional video, and is more and morepopular with audiences. Therefore,3D and multi-view video is one of the mainstreamdevelopment directions of today’s video technologies and applications, and has a very broadmarket prospects. But there are a number of key technologies that need to be solved: multi-viewtexture and depth acquisition, multi-view coding, transmission and decoding, and multi-viewrendering. In particular, how to obtain accurate depth information has become one of the hotresearch areas. The focus of this dissertation is how to introduce interactivity to the stereoscopiccontent, obtain depth information of the corresponding scene in the multi-viewpoint videosystem, and how to use the depth information for multi-view rendering, so that the audience canfreely select the viewpoint position.By building a system of free viewpoint video, we carried out the research work of three keytechnologies: depth maps estimation from a single viewpoint motion video, robust disparitymaps (depth maps) estimation from multi-view video, and virtual viewpoint synthesis based onDIBR. The major work and innovation are as follows:It is very difficult to estimate depth map from a single viewpoint motion video. By usingSFM (Structure from Motion) and the optical flow calculation, the image frame in the singleviewpoint motion video is converted into textures+depth map format, and each frame has anassociated camera pose. Firstly the algorithm makes use of the SFM to obtain scene sparserepresentation, the matching relationship of the feature point between image frames, and thecamera pose of each key frame. After a reference frame is given, the algorithm selects anotherimage frame which is concerned with the motion flow calculating by using the qualitymeasurement, in order to obtain the optimum depth maps. The algorithm does not carry out anydepth map interpolation calculation.In order to obtain a reliable depth map in low computational complexity, in this thesis, theglobal optimization methods integrated into the framework of the regional matching. There aretwo different ideas of the algorithm in order to extract depth information and to get more reliabledisparity map from the stereo image pair: One is the global error method based on energyminimization, and another is based on the linear region growing. In the block matchingalgorithm, In the search range of parallax, the global error energy minimization methodconstructs an error energy for each of the parallax matrix by block matching techniques. Linear growth to determine whether the error energy of correlation degree between a certain points withthe root point is less than the threshold value set in advance in the growth process. Every errormatrix is repeatedly perform mean filtering to find the minimum error energy, and thus to obtaina disparity map and depth map. The algorithm uses the smoothing function to do globaloptimization. In order to improve the reliability of the disparity map, the algorithm eliminatesunreliable forecast point due to occlusion area, by detecting the error energy in the disparity map.In the matching process, regional matching algorithm has been optimized through the applicationof recursive mean filtering fast calculation method and consequently it improves the efficiencyof the algorithm.Aiming at the ambiguity of the binocular stereo problem that may be caused by low textureareas and occlusions, a fast stereo matching based on Daisy feature descriptor and modifiedweight kernel is proposed in this thesis. Firstly, the local Daisy feature descriptors areconstructed fast and densely for both stereo pairs, the initial matching costs being calculatedfrom the features; two-pass aggregation with modified weight kernels for the reliable matchingcosts are applied to resolve ambiguity of feature similarities；Initial disparity map is obtained viaWinner-Takes-All optimization from them. Secondly, in order to improve the quality of disparitymap, this thesis adopts sequentially the refining procedure with modified bilateral filtering,symmetric consistency check and multi-directional weighted disparity extrapolation. Theexperiments indicate that this technique with concise structure and low complexity can improveeffectively the matching accuracy and obtain comparably accurate and piecewise smooth densedisparity map.This thesis presents a DIBR virtual viewpoint rendering algorithm based on the depth ofinformation processing. The algorithm makes use of camera parameters and depth of information,the reference viewpoint images and depth images are wrapped to the virtual viewpoint. Cracksand artifacts are removed by post-processing the projected images based on the depth ofinformation. Using the depth information, the remaining disocclusions are filled by inpaintingtechniques, and then these images are blended together. The experiments indicate that themethod is superior to the existing methods of generating virtual, not only in the subjectivequality but also in the objective quality. The study compares the quality of the composite imageof the multi-viewpoint rendering algorithms with the old, and analyses the influence of the videocompression.

Related Dissertations

  1. Effects of TLR2 on IL-8 and γ-IFN Secretion of Keratinocytes in Dermatophytic Infections,R756
  2. Palmprint image feature extraction method,TP391.41
  3. Sensor aided by video image reconstruction of 3D scene,TP391.41
  4. Depth Map Coding and Depth-based View Rendering in Free-view Video System,TP391.41
  5. Research and Implement on Digital Image 3D Stereoscope Display Algorithm,TP391.41
  6. Research and Implementation on 3D Information Reconstruction Based on Monocular Vision,TP391.41
  7. Mobile Robot Object Recognition and Localization Based on Monocular Vision,TP242.6
  8. The Key Techniques for Converting 2D to 3D Video Based on DIBR,TP391.41
  9. Research on Free View-point Video Capturing and Transmitting,TP391.41
  10. Study on the Nonstationary Wideband Interference Suppression in DSSS Systems,TN914.42
  11. A High Fidelity Mosaic Technology for Large Mural Image Based on SFM,TP391.41
  12. Watermarking of Free Viewpoint Television,TP309.7
  13. Stereoscopic Image Generation Based on Depth Maps,TP391.41
  14. Isolation and Identification of Side Population Cells from Human Tongue Squamous Carcinoma Tca8113 Cell Line Under Serum-free Culture Condition,R739.8
  15. Study on 3D Model Retrieval Technology Based on 3D Reconstruction,TP391.3
  16. Attack Detection Method Based on Time SFM Factors in Recommender System,F713.36
  17. Optimal control based on traffic for TCP / IP Congestion Control,TP393.02
  18. Studies on Neural Mechanism of Stress-induced Depression and Its Effects on Morphine Addiction,R749.4
  19. Thin film ferroelectric domains and their performance scanning force microscopy studies,TB43
  20. Support Vector Machine and the Applicaiton on the Prediction of Stock Price,F224
  21. Orbital frontal area of dopamine on gastric motility and its mechanism,R57

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile