Stereoscopic 3D (S3D) image retargeting aims to adjust aspect ratio of S3D images. To objectively and accurately assess the quality of different retargeted S3D images, a retargeted S3D image quality assessment database was constructed. Firstly, 45 original images were retargeted by eight representative retargeting algorithms with two retargeting scales to generate 720 retargeted S3D images. Then, the subjective quality evaluation score of each retargeted image was obtained via subjective testing. Finally, the subjective scores were converted to MOS (Mean Opinion Score) values. Based on all above, an objective quality assessment method was proposed for retargeted S3D images. In this method, three types of features including depth perception, visual comfort and image quality of left and right views were extracted to calculate the retargeted S3D image quality with the use of support vector regression prediction. Experimental results on the proposed database show that the proposed method has the Pearson linear correlation coefficient and the Spearman rank-order correlation coefficient higher than 0.82 and 0.81 respectively, demonstrating its superiority in retargeted S3D image visual quality assessment.