Based on computer vision and XGBoost, a method of shrimp vitality detection was proposed by taking Penaeus white shrimp as the research object. Firstly, track the movement trajectory of shrimp before and after stress to extract the movement behavior parameters. The color characteristics of shrimp were extracted according to the stressful red body phenomenon. Secondly, extract the texture characteristics of shrimp with water surface fluctuation forming under stress by using gray scale co-generation matrix, and use XGBoost algorithm to filter the evaluation factors, and determine the best weights of the evaluation factors by weighted fusion. Finally, the shrimp vitality intensity was detected according to the fused features. The results showed that the decision coefficient of the proposed method was 0.905 6 and the recognition accuracy was 98.61%, which improved by 6.63%, 2.05% and 1.61% compared with the single color, single texture and combined optical flow and texture methods, respectively.