iPhone Handheld Street Encounter Video
A highly technical prompt designed to simulate realistic, unedited-style iPhone street footage. It features specific camera behaviors like handheld shakes, autofocus delays, and CCD sensor artifacts to depict a candid street interaction between a model and a pedestrian.
Dit is een voorbeeld van een Seedance 2.0 prompt voor Portrait & Character . Gebruik de onderstaande kant-en-klare prompt om vergelijkbare afbeeldingen te genereren en controleer de Awesome Seedance 2.0 Video Prompts en de rechten voor commercieel gebruik voordat u de afbeeldingen hergebruikt.
Heb je de volledige set prompts nodig? Gebruik dan de Portrait & Character Ga naar het themacentrum voor meer gerelateerde voorbeelden, of open de Seedance 2.0 prompt catalogus Voor de volledige voorbeeldenindex, herbruikbare structuren en bronvermelding.
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Schrijfklare prompt
Rendered in the style of unprocessed authentic iPhone handheld video footage, with all camera settings on automatic and no post-processing color grading or special effects. The image includes realistic handheld micro-shaking and the sense of the operator's (bystander) breathing, with the lens naturally sinking or tilting due to walking before quickly correcting. Autofocus occasionally searches, delays, or briefly loses focus, especially during following motions or hand movements. Automatic white balance naturally switches between cool and warm tones as street light and tree shadows change. The overall image is flat, preserving real lens flares, slight chromatic aberration at the edges, and optical imperfections like motion blur. Simulates CCD sensor effects with slight vertical smearing, color bleeding, grain noise, and purple/green fringes on high-contrast edges. Only uses in-camera natural environmental sound effects, including street traffic, footsteps, and wind through leaves; the microphone may slightly distort when people speak. Uses a street third-person bystander perspective (shot by a nearby passerby), with lens movement following the bystander's instinctive reactions. Retain 100% of the model's age, facial features, bone structure, eye distance, jaw geometry, temperament, skin tone, and hairstyle from the reference image. No skin smoothing, over-softening, or shifting toward an 'average face.' 15-second timeline (Scene: Phone misunderstanding -> Woman thinks she's being insulted -> Embarrassed turn -> Reversal): At 0s, the lens shakes slightly from a bystander perspective, aiming at a street lined with golden sycamores. A slender, long-haired woman in a mask and specific outfit walks toward the camera. On the right, a man in a black jacket is on the phone. Ambient traffic sounds are natural. Autofocus locks on their interaction; slight overexposure and CCD grain are visible. At 1-3s, as the woman approaches, the man yells into his phone, 'You dare go out dressed like that?' The woman stops and glares angrily. The man looks at her innocently and shows his phone screen. The lens follows slightly with a brief autofocus search and noticeable CCD smearing. At 4-7s, the woman looks embarrassed, apologizes, and continues walking. The man continues his loud phone conversation. The lens follows her naturally with slight walking jitters. At 8-11s, after walking away, the woman suddenly turns back and raises her hand as if to strike the man. The man looks bewildered and shows his phone again. The bystander lens turns quickly to follow, with autofocus lag and handheld jitters intensifying. Microphones capture the angry woman and the man's helpless explanation. At 12-15s, she finally waves dismissively and leaves. The lens tilts slightly as the bystander shifts weight. The overall feel is an unprocessed, handheld street interaction with documentary-level natural imperfections.
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Hergebruik en bronvermeldingen
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