The structure of cubicles can hinder cows’ movements when transitioning between postures, leading to atypical motion patterns. Assessing posture transitions relies on visual observations. This study presents a framework for complementing these assessments with kinematic measurements using 3D pose estimation. A total 809 rising and 791 lying down posture transitions were recorded over 12 cubicles by 7 synchronized cameras and processed with 3D pose estimation locating the position of the poll, withers, T13 and sacrum. First, the displacement of the keypoints was used to detect phases of the posture transitions. This detection was compared with visual observations of 200 recordings. The average mean absolute difference in detected timestamps between human and machine across all phases was 0.5 s (average σ = 0.7) and was under 0.9 s for all phases. Second, indicators were scored based on spatial use and duration, and their distribution compared to existing thresholds. We observed that 59.9 % of rising bouts and 29.1 % of lying down bouts exceeded at least one threshold. Rising delay occurred in 2.8 % of rising bouts and backwards crawling in 59.2 %. Lying down duration exceeded the threshold in 28.9 % of bouts, and rear limbs shifting duration in 8.3 %. Side lunge had a binary threshold which was not adapted to continuous sensor data. Finally, we investigated the association between indicators and found distinct dimensions for head lunge and crawling. We conclude that 3D pose is useful to score posture transition indicators, and that several indicators should be used together to capture distinct dimensions. © 2025 Elsevier B.V., All rights reserved.