To achieve non-contact and continuous monitoring of body length in Micropterus salmoides and overcome the stress damage and subjective error associated with traditional manual measurement, this paper proposes an improved YOLOv8-based multi-target tracking framework for intensive recirculating aquaculture systems. The system employs a geometric measurement framework based on monocular vision that achieves conversion from pixel coordinates to actual body length through camera calibration, water-surface refraction correction, and pose projection correction. Under a collaborative optimization framework integrating detection and tracking, the model incorporates multi-scale feature enhancement, lightweight re-identification (ReID), and a robust data association mechanism, which improves system stability under conditions of high fish density, variable illumination, and turbid water. A shallow feature fusion path is introduced to enhance small-target perception, and a MobileNetV3_ReID model is adopted to extract highly discriminative appearance features, which improves identity consistency while maintaining model compactness. In the data association stage, a hybrid cost matrix integrating IoU, cosine similarity, and motion consistency is constructed, and optimal matching is realized through the Hungarian algorithm. Dynamic threshold adjustment and an exponential moving-average feature-update strategy are introduced to effectively suppress identity switching. Experiments were conducted on an overhead video dataset of Micropterus salmoides collected at a recirculating aquaculture system facility. The results show that the proposed method achieves 82.7% mAP50 while maintaining a real-time throughput of 88 FPS, with MOTA reaching 76.9% and IDF1 reaching 81.5%—the latter representing an improvement of 3.2 percentage points over BoT-SORT and 5.3 percentage points over the YOLOv8 baseline tracker. The number of identity switches (IDSW) decreased from 89 in the baseline configuration to 39, a reduction of 56.2%. Crucially, these component-level improvements translate into a body length error (BLE) of 5.2 ± 1.8% (MAE = 1.35 cm, Pearson r = 0.972), representing a 38.8% improvement over the baseline BLE of 8.5% and satisfying the 5–10% tolerance required for aquaculture growth monitoring. Ablation analysis confirms that both detection enhancements (contributing −1.3% BLE) and tracking optimizations (contributing −2.0% BLE) are necessary to achieve this application-level accuracy.

Ammonia nitrogen is one of the most common environmental stressors in aquaculture water environments, and its accumulation can induce physiological disturbance, altered ventilation regulation, and abnormal behavioral responses in fish. To achieve non-invasive quantitative characterization of rainbow trout responses to ammonia nitrogen stress, this study developed a computer-vision-based framework for the integrated analysis of locomotor behavior and ventilation activity. Rainbow trout were exposed to four ammonia nitrogen concentrations: 0, 15, 30, and 60 mg/L. A total of 16 rainbow trout were used in this study, with an average body length of 14.0 ± 1.0 cm and an average body weight of 38.65 ± 2.42 g. The fish were assigned to four experimental aquaria, with four fish maintained in one aquarium for each TAN treatment. Stereo videos for locomotor behavior analysis and monocular mouth-region videos for ventilation analysis were simultaneously collected, and the final 5 min of each recording was analyzed. YOLOv11n, multi-object tracking, and stereo vision were used to extract three-dimensional position sequences of rainbow trout and calculate the amount of exercise, average swimming speed, and spatial distribution. Meanwhile, optical-flow analysis was applied to quantify mouth opening–closing motion and estimate ventilation frequency. The results showed that with increasing ammonia nitrogen concentration, rainbow trout locomotor behavior tended to be suppressed, with average swimming speed showing the clearest decrease, whereas ventilation frequency continuously increased. Average swimming speed decreased from 3.83 cm/s in the 0 mg/L group to 1.03 cm/s in the 60 mg/L group, while ventilation frequency increased from 84.91 breaths/min to 133.43 breaths/min. Compared with locomotor indicators, ventilation frequency showed a more stable response to changes in ammonia nitrogen concentration. This study achieved the synchronous quantification of rainbow trout locomotor behavior and ventilation activity, revealing a differentiated response pattern characterized by enhanced ventilation and suppressed locomotor behavior under acute ammonia nitrogen stress. These findings provide a methodological reference for fish stress assessment and risk warning in aquaculture environments.