1. 1 2D TO 3D IMAGE AND VIDEO CONVERSION

2. INTRODUCTION The goal is to take already existing 2D content, and artificially produce the left and right views. Uses a sense of depth to get a sense of realism. Evolved due to the urgent need for 3D contents to the 3D hardwares. 2

3. TERMINOLOGIES USED Stereoscopy – present two offset images separately to the left and right eye of the viewer. Monocular images – presents single image with increased field of view while depth perception is limited. Stereo rendering – producing a stereo pair. DIBR – Depth Image Based Rendering is a technique for producing 3D video sequence by generating new virtual views for an original video sequence and the depth information that has been extracted from the original sequence. 3

4. DEPTH AND DISPARITY Depth refers to the distance of the surfaces of scene objects from a view point Cubic Structure Depth Map: Nearer is darker Disparity refers to the distance between two corresponding points in the left and right image of a stereo pair 4

5. APPROACHES TO CONVERSION Two basic approaches to 2D to 3D conversion: Automatic Approach in which no operator intervention is needed and a computer algorithm estimates the depth for a single image. Semi Automatic Approach that requires a human operator’s intervention to assign depth to various parts of an image or video sequence 5

6. STEPS IN CONVERSION Two basic steps involved in a typical 2D to 3D conversion process depth estimation for a given 2D image. depth based rendering of a new image inorder to form a stereo pair. 6

7. TECHNIQUES FOR CONVERSION Most predominant techniques are by using: Motion Scene features Miscellaneous methods 7

8. USING MOTION Using motion estimation to determine the depth or disparity of the scene. Underlying mechanism: - objects closer to camera move faster - objects that are far from camera move slower 8

9. USING MOTION Advantages Stable and comfortable stereoscopic videos. Disadvantages Two objects, one moving fast but depth quite far and another one moving with same speed but closer can be interpreted as having same depth. 9

10. USING SCENE FEATURES Most popular method for converting 2D monocular video sequences into 3D. Analyses the features of the scene of interest. 10

11. EDGE Edge information to determine stereoscopic content from 2D data. Group regions of pixels together using edge information. Advantages Comfortable 3D effect. USING SCENE FEATURES 11

12. USING SCENE FEATURES COLOR Color information directly for determining depth maps from monocular video sequences. Each intensity belong to roughly the same kind of objects and thus the same depth value. 12

13. USING SCENE FEATURES Advantages Simplicity of implementation. Disadvantages Components themselves could misrepresent the depth of objects in certain situations. 13

14. MISCELLANEOUS METHODS Methods that do not fall into any of above categories. MACHINE LEARNING ALGORITHM An automatic approach Uses images available in a large repository and automatically select suitable ones for depth recovery. 14

15. MISCELLANEOUS METHODS Advantages Extremely fast Better in terms of cumulative performance over datasets Comfortable 3D experience. Disadvantages Not completely void of distortions. 15

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