In this letter, the colored point cloud quality assessment in Augmented Reality (AR) environment was fully studied through subjective test. Firstly, we present a point cloud dataset, named Point Cloud Quality Dataset-AR (PCQD-AR), including ten reference point clouds and their 90 distorted versions, which were encoded by the reference software of Video-based Point Cloud Compression (V-PCC) under different pairs of geometry and texture quantization parameters. Then, the impact of geometry and texture distortions on perceived quality of point clouds in the AR environment was discussed in detail. Moreover, we evaluate the performance of existing objective point cloud quality assessment metrics on the proposed dataset. The subjective dataset including the values of Mean Opinion Score (MOS) will be released after acceptance.