Research on Depth Information Estimation for Video Objects

2014 ◽  
Vol 513-517 ◽  
pp. 3797-3800 ◽  
Author(s):  
Wen Bin Wang ◽  
Dao Yuan Liu ◽  
Yu Qin Yao
Keyword(s):  
Background Subtraction ◽  
Motion Parallax ◽  
Depth Map ◽  
3D Video ◽  
Block Matching ◽  
Depth Information ◽  
Motion In Depth ◽  
Video Objects ◽  
2D To 3D ◽  
Conversion Technology

Through the analyzing of the color, motion, parallax and the degree of clarity in scene-all the elements presented on the 2D video, People can produce 3D video smoothly. The paper introduces a kind of pick-up algorithm of depth map, the method of combining the abstraction of motion in depth based on the block matching and the abstraction of background in depth on the basis of background subtraction. The extracted map can be applied to the video conversion technology of "2D to 3D".

Motion-Based Depth Estimation for 2D to 3D Video Conversion

2016 ◽  
Vol 20 (1) ◽  
pp. 13-25 ◽  
Author(s):  
Fan Guo ◽  
◽  
Jin Tang ◽  
Beiji Zou ◽  
Keyword(s):  
Motion Parallax ◽  
Depth Map ◽  
Bilateral Filter ◽  
Depth Estimation ◽  
3D Video ◽  
Local Motion ◽  
Single View ◽  
Motion Type ◽  
Visual Artifacts ◽  
2D To 3D

Recent advances in 3D have increased the importance of stereoscopic content creation and processing. Therefore, converting existing 2D videos into 3D videos is very important for growing 3D market. The most difficult task in 2D-to-3D video conversion is estimating depth map from single-view frame images. Thus, in this paper, we propose a novel motion-based 2D to 3D video conversion method. The method first determines the motion type using the optical flow estimation. Then, different depth estimation processes are performed based on the motion type. For global motion, the depth from motion parallax provides the final depth map. For local motion, the depth from template together with the bilateral filter is used to produce the depth map. Finally, the left- and right-view images are synthesized to generate realistic stereoscopic results for viewers. During the process, the visual artifacts of the synthesized virtual views are effectively eliminated by recovering the separation and loss of foreground objects. A comparative study and quantitative evaluation with other conversion methods are carried out, which demonstrate that better overall quality results may be obtained using the proposed method.

Hardware/Software Co-Design of 2D-to-3D Video Conversion on FPGA

2013 ◽  
Vol 284-287 ◽  
pp. 3230-3234
Author(s):  
Thomas Schumann ◽  
Herbert Krauß ◽  
Yeong Kang Lai ◽  
Yu Fan Lai
Keyword(s):  
Image Inpainting ◽  
3D Video ◽  
View Synthesis ◽  
Image Warping ◽  
Depth Information ◽  
3D Image ◽  
Hole Filling ◽  
Synthesis Algorithm ◽  
3D Image Warping ◽  
2D To 3D

With advances in technology, 3D video technology becomes possible and attractive. However, there are still many pre-recorded 2D videos/images which need to get transferred to 3D. Hence this paper presents a high quality view synthesis algorithm and architecture for 2D-to-3D video conversion. During the process of view synthesis, the monocular depth information together with the intermediate view is synthesized to the left-eye and right-eye view. The proposed view synthesis algorithm consists of two parts: 3D image warping and inpainting (hole filling). 3D image warping transforms a 2D camera image plane to a 3D coordinate plane. However the integer grid points of the reference are warped to irregularly spaced points in the virtual view, resulting in occlusion problems. Thus inpainting is needed to fix the virtual images. The proposed algorithm shows an improved PSNR gain of 0.2~1.5dB. We adopt hardware/software co-design to accomplish the proposed view synthesis algorithm. For this we implemented the image inpainting on a FPGA device and the remaining algorithm in software.

scholarly journals Pattern-based Depth Map Generation for Low-complexity 2D-to-3D Video Conversion

2015 ◽  
Vol 15 (2) ◽  
pp. 31-39
Author(s):  
Chan-Hee Han ◽  
Hyun-Soo Kang ◽  
Si-Woong Lee
Keyword(s):  
Depth Map ◽  
Low Complexity ◽  
3D Video ◽  
Map Generation ◽  
2D To 3D

scholarly journals REAL-TIME DEPTH MAP ESTIMATION FROM INFRARED STEREO IMAGES OF RGB-D CAMERAS

2021 ◽  
Vol V-2-2021 ◽  
pp. 107-112
Author(s):  
J. Zhong ◽  
M. Li ◽  
X. Liao ◽  
J. Qin ◽  
H. Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Block Size ◽  
Depth Map ◽  
Measurement Range ◽  
Block Matching ◽  
Depth Information ◽  
Depth Maps ◽  
Sensing Systems ◽  
Global Matching ◽  
Efficient Matching

Abstract. RGB-D cameras are novel sensing systems that can rapidly provide accurate depth information for 3D perception, among which the type based on active stereo vision has been widely used. However, there are some problems exiting in use, such as the short measurement range and incomplete depth maps. This paper presents a robust and efficient matching algorithm based on semi-global matching to obtain more complete and accurate depth maps in real time. Considering characteristics of captured infrared speckle images, the Gaussian filter is performed firstly to restrain noise and enhance the relativity. It also adopts the idea of block matching for reliability, and a dynamic threshold selection of the block size is used to adapt to various situation. Moreover, several optimizations are applied to improve precision and reduce error. Through experiments on the Intel Realsense R200, the excellent capability of our proposed method is verified.

A New Approach of 2D-to-3D Video Conversion and Its Implementation on Embedded System

2011 ◽  
Vol 58-60 ◽  
pp. 2552-2557
Author(s):  
Hao Jun Li ◽  
Yue Sheng Zhu
Keyword(s):  
Embedded System ◽  
Prediction Method ◽  
3D Video ◽  
Video Sequences ◽  
Video Frame ◽  
Depth Information ◽  
Video Scene ◽  
Camera Position ◽  
The Relationship ◽  
2D To 3D

Rather than based on the stereo vision principle and the relationship between the camera position and the video scene objects used in most of current 2D-to-3D video conversion algorithms, a new prediction method of video depth information based on video frame differences is proposed and implemented on an embedded platform in this paper. 3D stereoscopic video sequences are generated by using the original 2D video sequences and the depth information. The theoretical analysis and experimental results have showed that the proposed method is more feasible and efficiency compared with the current algorithms.

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