Stereoscopic　Image　Retargeting　(SIR)　aims　to　adapt　stereoscopic　images　and　videos　to　3D　display　devices　with　various　aspect　ratios　by　emphasizing　the　important　content　while　retaining　surrounding　context　with　minimal　visual　distortion.　To　address　the　issue　of　SIR　evaluation,　this　paper　presents　a　new　objective　quality　assessment　method　for　retargeted　stereopairs　by　combining　image　quality　and　depth　perception　measures.　Specifically,　the　image　quality　measure　is　conducted　between　the　source　and　retargeted　intermediate　views　generated　by　the　view　synthesis　method　to　characterize　the　geometric　distortion　and　content　loss　of　the　retargeted　stereopair,　while　several　depth-aware　features　are　extracted　to　measure　the　visual　comfort/discomfort　and　depth　sensation　when　human　views　a　3D　scene.　Then,　the　extracted　features　are　integrated　into　an　overall　perceptual　quality　prediction.　Experiment　results　on　NBU　SIRQA　and　SIRD　databases　verify　the　superiority　of　our　method.