A depth-aware character generator for 3DTV

In 3DTV, it is known that video captions and graphics should be inserted at proper scene depth positions, to prevent possible viewing discomfort. We propose a character generator that automatically analyzes the scene disparities and determines the proper depth of the graphic object to be inserted. The challenge is that the disparity range estimation from feature correspondences is severely affected even by a few outliers, whereas nauml;ve SURF or BRIEF matching produces a considerable amount of outliers. We propose a multiple-hypothesis feature matching algorithm that considers the disparity coherence between adjacent features, with which most mismatches can be removed according to the reliability aggregated from the neighboring features. To estimate the accurate disparity range from the feature correspondences, a disparity histogram is computed and filtered by a space-time kernel to suppress the effect of incorrect disparities. We also propose the disparity-depth conversion in the asymmetric view frustum which is used for the stereoscopic rendering of graphics. Experimental results show that a 3D graphic object is successfully inserted at the desired depth which is obtained from the proposed disparity range estimation and disparity-depth conversion.