We describe a new algorithm to construct pseudo-3-D videos out of conventional 2-D videos at the viewing end, where no additional 3-D information is attached at the source of 2-D video production. We name such constructed videos pseudo-3-D on the grounds that the converted video is not true 3-D but presents a perceptual 3-D effect when viewed with a pair of polarized glasses. The proposed algorithm consists of two video processing stages: (1) semantic video object segmentation; and (2) estimation of disparities. In the first stage, we propose a constrained region-growing and filtering approach to improve existing segmentation techniques based on change detections. Such a processing stage ensures that disparities are estimated in terms of semantic video objects rather than textured regions, and thus improve the pseudo-3-D effect in terms of human visual perception. In the second stage, we propose a video object (VO)-size-based disparity estimation to construct additional video frames for the proposed pseudo-3-D video conversion. Experiments carried out demonstrate that the proposed algorithm effectively produces perceptually harmonious pseudo-3-D videos with the advantages of simplicity and low computing cost.