In this article, an automatic stereoscopic video conversion scheme which accepts MPEG-encoded videos as input is proposed. Our scheme is depth-based, relying on spatio-temporal analysis of the decoded video data to yield depth perception cues, such as temporal motion and spatial contrast, which reflect the relative depths between the foreground and the background areas. Our scheme is shot-adaptive, demanding that shot change detection and shot classification be performed for tuning of algorithm or parameters that are used for depth cue combination. The above-mentioned depth estimation is initially block-based, followed by a locally adaptive joint trilateral upsampling algorithm to reduce the computing load significantly. A recursive temporal filter is used to reduce the possible depth fluctuations (and also artifacts in the synthesized images) resulting from wrong depth estimations. The traditional Depth-Image-Based-Rendering algorithm is used to synthesize the left-and right-view frames for 3D display. Subjective tests show that videos converted by our scheme provide comparable perceived depth and visual quality with those converted from the depth data calculated by stereo vision techniques. Also, our scheme is shown to outperform the well-known TriDef software in terms of human's perceived 3D depth. Based on the implementation by using "OpenMP" parallel programming model, our scheme is capable of executing in real-time on a multi-core CPU platform.

In this article, we propose a 2D to 3D video conversion scheme for MPEG videos. The difficulty for 2D/3D conversion problem lies on depth estimation/ assignment with insufficient information. Our depth assignment is based on the analyses of multiple cues, e.g., motion parallax, atmospheric perspective, texture gradient, linear perspective, and relative height, separately for the foreground objects and the background area. To fit more kinds of videos, the proposed depth assignment scheme is content-adaptive by segmenting a video into shots and classifying each of them into three categories for different conversion schemes. Subjective experiments show that the 3D stereo video generated by using our depth assignment scheme and the Depth Image Based Rendering (DIBR) technique presents little difference to that created based on the depth ground truths.