This article analyzes the integration of mobilegraphy, camera angles, and camera movements into artificial intelligence (AI) systems through prompt engineering in the process of neuro-photoshoots. Although modern text-to-image diffusion models offer significant capabilities for generating visual content, the quality of their output largely depends on the accuracy and structural clarity of the input prompt. The study formalizes camera angles (eye-level, low angle, high angle, etc.) and camera movements (pan, tilt, dolly, handheld) within a structured prompt format in combination with mobilegraphy principles. The results demonstrate that such an approach significantly enhances the realism, depth, and cinematic quality of generated images.
| Mualliflar | Kayumova , Gulshan, Fayzullayeva, Dilora, Yigitaliyev , Boburmirzo |
|---|---|
| Jurnal | Марказий Осиёда медиа ва коммуникациялар |
| Nashr sanasi | 2026-05-22 |
| Son | 13 |
| Til | O‘zbek |
| DOI | 10.62499/ijmcc.vi13.296 |
DOI: 10.62499/ijmcc.vi13.296 · Maqolaning asl sahifasi
визуальный реализм, diffusion-модели, движения камеры, ракурсы камеры, промпт-инжиниринг, мобилография, нейрофотосессия, neyrofotosessiya, mobilografiya, prompt muhandisligi, kamera rakurslari, kamera harakatlari, diffusion modellar, vizual realizm, neuro-photoshoot, mobilegraphy, prompt engineering, camera angles, camera movements, diffusion models, visual realism
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