（一）运镜的定义、作用与 AI 实现逻辑

运镜即镜头的运动，是影视制作、视频拍摄及 AI 生成图像中，通过改变镜头位置、角度、焦距等方式捕捉画面的技术手段。它是影视语言的核心组成部分，能影响观众视觉感受、传达情感、推动叙事并塑造氛围。在 AI 生成图像中，运镜的实现依赖提示词引导 —— 通过明确 “运镜类型（如推、拉、环绕）+ 主体描述 + 风格限定” 等关键词，让 AI 生成具有动态趋势的画面，使静态图像呈现 “运动感”。

Camera movement refers to the technical method of capturing images by changing the lens position, angle, focal length, etc., in film and television production, video shooting, and AI-generated images. It is a core component of film and television language, which can affect the audience's visual experience, convey emotions, promote narration, and shape the atmosphere. In AI-generated images, the realization of camera movement relies on prompt guidance—by specifying keywords such as "camera movement type (e.g., push, pull, surround) + subject description + style restriction", AI is enabled to generate images with dynamic trends, endowing static images with a "sense of movement".

（二）首尾帧技术的核心机制与应用价值

首尾帧技术是通过 AI 实现流畅长镜头效果的关键手段，指上传视频的首帧与尾帧图片后，AI 基于 GAN（生成对抗网络）等模型，分析两张图片的构图、风格及主体特征，自动填补中间过渡帧，形成自然连贯的视频片段。目前可灵、VIDU、即梦等工具均支持该功能，其核心价值在于大幅降低长镜头创作门槛 —— 无需复杂设备与专业拍摄，仅通过 “两图 + 提示词” 即可生成电影质感片段，显著节省创作成本。

The first/last frame technology is a key method to realize smooth long-shot effects through AI. It refers to uploading the first and last frame images of a video, after which AI, based on models such as GAN (Generative Adversarial Network), analyzes the composition, style, and subject features of the two images, automatically fills in the intermediate transition frames, and forms a naturally coherent video clip. Currently, tools such as Keling, VIDU, and Jimeng support this function. Its core value lies in greatly lowering the threshold for long-shot creation—without complex equipment and professional shooting, film-quality clips can be generated only through "two images + prompts", significantly saving creation costs.

（三）AI 视觉动态表达的核心工具与技术特点

AI 视觉动态表达依赖两类核心工具：一是 AI 图像生成工具（如 MidJourney），主要用于制作首尾帧图片及单张运镜效果图像，通过精准提示词控制画面主体、风格与动态趋势；二是 AI 图生视频工具（如 VIDU），专注于首尾帧过渡与长镜头生成，支持推、拉、摇、移等运镜效果模拟，能自动生成符合提示词的过渡逻辑。两类工具的协同使用 ——“图像工具制帧 + 视频工具生成过渡”，是实现 AI 视觉动态创作的主流流程，兼具灵活性与高效性。

AI visual dynamic expression relies on two types of core tools: one is AI image generation tools (e.g., MidJourney), mainly used to create first/last frame images and single images with camera movement effects, controlling the image subject, style, and dynamic trends through precise prompts; the other is AI image-to-video tools (e.g., VIDU), focusing on first/last frame transition and long-shot generation, supporting the simulation of camera movement effects such as push, pull, pan, and tilt, and can automatically generate transition logic that conforms to prompts. The collaborative use of the two types of tools—"image tools for frame creation + video tools for transition generation"—is the mainstream process for AI visual dynamic creation, which is both flexible and efficient.