The PoseAnimate framework is a zero-shot reconstruction-based image-to-video (I2V) approach for generating pose-controllable character animation videos. It introduces a Pose-Aware Control Module (PACM) that optimizes text embeddings based on original and target pose conditions to align actions while maintaining scene consistency. Additionally, a Dual Consistency Attention Module (DCAM) is implemented to address disruptions caused by introducing new target poses, ensuring smooth temporal progression. To enhance fine-grained detail perception, a Mask-Guided Decoupling Module (MGDM) enables independent spatial attention fusion for character and background regions. Furthermore, a Pose Alignment Transition Algorithm (PATA) ensures pose alignment and smooth transitions for various target pose sequences. By combining these modules, PoseAnimate efficiently generates high-quality character animation videos without the need for network training.