Hair is likely one of the most exceptional options of the human physique, impressing with its dynamic qualities that convey scenes to life. Research have constantly demonstrated that dynamic components have a stronger enchantment and fascination than static photos. Social media platforms like TikTok and Instagram witness the every day sharing of huge portrait images as individuals aspire to make their photos each interesting and artistically fascinating. This drive fuels researchers’ exploration into the realm of animating human hair inside nonetheless photos, aiming to supply a vivid, aesthetically pleasing, and delightful viewing expertise.
Current developments within the subject have launched strategies to infuse nonetheless photos with dynamic components, animating fluid substances comparable to water, smoke, and fireplace inside the body. But, these approaches have largely ignored the intricate nature of human hair in real-life images. This text focuses on the inventive transformation of human hair inside portrait pictures, which includes translating the image right into a cinemagraph.
A cinemagraph represents an progressive quick video format that enjoys favor amongst skilled photographers, advertisers, and artists. It finds utility in varied digital mediums, together with digital commercials, social media posts, and touchdown pages. The fascination for cinemagraphs lies of their potential to merge the strengths of nonetheless photos and movies. Sure areas inside a cinemagraph function refined, repetitive motions in a brief loop, whereas the rest stays static. This distinction between stationary and shifting components successfully captivates the viewer’s consideration.
By way of the transformation of a portrait picture right into a cinemagraph, full with refined hair motions, the concept is to reinforce the picture’s attract with out detracting from the static content material, making a extra compelling and interesting visible expertise.
Present methods and industrial software program have been developed to generate high-fidelity cinemagraphs from enter movies by selectively freezing sure video areas. Sadly, these instruments aren’t appropriate for processing nonetheless photos. In distinction, there was a rising curiosity in still-image animation. Most of those approaches have targeted on animating fluid components comparable to clouds, water, and smoke. Nonetheless, the dynamic habits of hair, composed of fibrous supplies, presents a particular problem in comparison with fluid components. Not like fluid aspect animation, which has acquired intensive consideration, the animation of human hair in actual portrait images has been comparatively unexplored.
Animating hair in a static portrait picture is difficult as a result of intricate complexity of hair buildings and dynamics. Not like the graceful surfaces of the human physique or face, hair includes a whole bunch of hundreds of particular person elements, leading to complicated and non-uniform buildings. This complexity results in intricate movement patterns inside the hair, together with interactions with the pinnacle. Whereas there are specialised methods for modeling hair, comparable to utilizing dense digicam arrays and high-speed cameras, they’re usually expensive and time-consuming, limiting their practicality for real-world hair animation.
The paper offered on this article introduces a novel AI methodology for routinely animating hair inside a static portrait picture, eliminating the necessity for consumer intervention or complicated {hardware} setups. The perception behind this method lies within the human visible system’s lowered sensitivity to particular person hair strands and their motions in actual portrait movies, in comparison with artificial strands inside a digitalized human in a digital surroundings. The proposed answer is to animate “hair wisps” as an alternative of particular person strands, making a visually pleasing viewing expertise. To realize this, the paper introduces a hair wisp animation module, enabling an environment friendly and automatic answer. An summary of this framework is illustrated under.
The important thing problem on this context is find out how to extract these hair wisps. Whereas associated work, comparable to hair modeling, has targeted on hair segmentation, these approaches primarily goal the extraction of the complete hair area, which differs from the target. To extract significant hair wisps, the researchers innovatively body hair wisp extraction for instance segmentation drawback, the place a person phase inside a nonetheless picture corresponds to a hair wisp. By adopting this drawback definition, the researchers leverage occasion segmentation networks to facilitate the extraction of hair wisps. This not solely simplifies the hair wisp extraction drawback but in addition permits the usage of superior networks for efficient extraction. Moreover, the paper presents the creation of a hair wisp dataset containing actual portrait images to coach the networks, together with a semi-annotation scheme to supply ground-truth annotations for the recognized hair wisps. Some pattern outcomes from the paper are reported within the determine under in contrast with state-of-the-art methods.
This was the abstract of a novel AI framework designed to remodel nonetheless portraits into cinemagraphs by animating hair wisps with pleasing motions with out noticeable artifacts. If you’re and wish to be taught extra about it, please be at liberty to discuss with the hyperlinks cited under.
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Daniele Lorenzi acquired his M.Sc. in ICT for Web and Multimedia Engineering in 2021 from the College of Padua, Italy. He’s a Ph.D. candidate on the Institute of Data Know-how (ITEC) on the Alpen-Adria-Universität (AAU) Klagenfurt. He’s at the moment working within the Christian Doppler Laboratory ATHENA and his analysis pursuits embody adaptive video streaming, immersive media, machine studying, and QoS/QoE analysis.