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As computer processing and digital imaging capabilities advance, Augmented Reality (AR) is becoming more prevalent. Smartphones and other handheld devices have AR capabilities, which permit users to capture, view and render real-world images in real-time. AR-enabled smartphones and other handheld devices permit users to see or record scenes that include the appearance of characters, objects, or objects. Digitally added to the scene.
AR environments add layers to digital images and videos. It is essential that the layers are compatible with the video and images to create realistic AR scene. The lighting, texture, and other visual characteristics ofAR layers play a large part in making the finer details of AR layers blend into the actual-world images and videos. Particularly, if the visual characteristics of the AR layers don’t blend into the background of the real world and the AR scene may appear fake or unnatural in some way.
Some AR applications require specific visual properties to work. AR components. For instance when you use AR devices to test makeup, precise mixing of AR layers with real-world photos or videos is crucial to the functionality of ARlayers. Particularly, various lights, skin tones and makeup ingredients can create wildly different appearance in real-world settings. The hue of a particular makeup product may be very inaccurate without accurate blend. The user may not be able to see exactly how the makeup would appear in actual environments.
Conventional AR systems that utilize makeup or other facial accessories in AR environments typically apply a color to a makeup layer in an AR environment in the HSV/LAB color space. However, even with AR lighting effects, however, the traditional AR systems typically produce an inaccurate appearance of AR makeup/materials relative to the real-world environment due to varied lighting conditions, user skin tones, and/or makeup/materials. There are a variety of disadvantages with traditional AR systems.
A variety of embodiments provide advantages or resolve problems in the art. These systems, methods and non-transitory storage media for computer-readable data generate an augmented reality makeup which has realistic lighting and color. The disclosed systems can take luminance frequencies of digital video and mix the makeup selection with the extracted luminance frequency. The disclosed systems transform the blended color into the LAB space and then adjust the lightness of the blended color by applying one or more of several shading models to it based on the makeup selected (e.g. glitter, gloss matte metallic). When the makeup choice material is applied to the blended color to alter the lightness it is then converted by the disclosed systems it back into the RGB space that can be used in the digital video stream.
In one or more of the embodiments the disclosed system employs localized tone mapping (e.g. average luma andluma range) to the digital video stream. The disclosed systems can reduce the size of the video stream and calculate the luma values (e.g. the average luma value or luma range) for each section of the digital stream. The disclosed systems can then alter the luma values of the various sections based on a predetermined threshold for luma, by remapping the hue of each pixel in an s-curve generated fromthe calculated luma values. The disclosed systems use downsampled digital stream processing and processes that smooth the appearance of the user’s faces with a guided filter which leverages images based on aluma. These disclosedsystems are able to precisely and quickly duplicate the colors of makeup based on the tone of the skin and lighting conditions, all the while simultaneously efficiently using computing resources.
Additional advantages and features of one or more embodiments of the disclosed disclosure will be described in the description which follows, and in part will be apparent from the description, or may be learned through the application of the example embodiments.
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Are you looking for similar patents? Here are the steps to follow:
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Write down a brief and precise description of the invention. Do not use generic terms such as “device”, “process,” or “system”. Instead, think about synonyms for the terms you selected initially. Also, keep track of important technical terms and keywords.
Use the questions below to help you identify key words or concepts.
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- What is the goal of this invention?
- What are the terms in the technical field and the keywords that define the nature of an invention? To assist you in finding the appropriate terms, use an online dictionary of technical terms.
2. These terms will allow you to find pertinent Cooperative Patent Classifications using the Classification Search Tool. If you’re unable to find the right classification to describe your invention, scan through the Schemas of classes (class schedules). If you do not get results using the Classification Text Search, you may want to consider replacing the words for describing your invention using synonyms.
3. Review 3. Go over the CPC Classification Definition to determine the validity of the CPC classification you’ve discovered. If the classification you have selected is a blue box that has the letter “D” to its left, clicking on the link will direct you to a CPC classification description. CPC classification definitions can help identify the specific classification’s scope, so you are sure to select the one you consider to be the most relevant. These definitions may also include research tips or other suggestions which could prove useful in further study.
4. Retrieve patent documents with the CPC classification from the Patents Full-Text and Image Database. You can search and select the relevant patent publications by first focusing on abstract and the drawings that are representative.
5. This list of patent publications is the best to examine for connections with your invention. Pay attention to the claims and specification. You may find additional patents by referring to the patent examiner and the applicant.
6. Find patent applications published in the public domain using the CPC classification you chose in Step 3 of the Applications Full-Text and Image Database. It is also possible to use the same strategy of searching you used in step 4 to limit your search results to just the most relevant patents by reading the abstracts and drawings on every page. Next, carefully examine the patent applications published and pay particular attention to the claims and the additional drawings.
7. You can find additional US patent publications using keyword searching in AppFT or PatFT databases, and also the classification search of patents that are that are not issued by the United States per below. Additionally, you can use web search engines to find non-patent-related literature disclosures about inventions. Examples:
- Add keywords to your search. Keyword searches may turn up documents that are not well-categorized or have missed classifications during Step 2. For example, US patent examiners often supplement their classification searches with keyword searches. Think about the use of technical engineering terminology rather than everyday words.
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- Japan Patent Office (JPO) – with access to machine translations of Japanese patents.
- World Intellectual Property Organization (WIPO) offers PATENTSCOPE with a full-text search of published international patent applications and machine translations for some documents, as well as a list of international patent databases.
- Korean Intellectual Property Rights Information Service (KIPRIS)
- State Intellectual Property Office (SIPO) with machine translation of Chinese patents.
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To review your search, you can hire a registered patent attorney to assist. A preliminary search will help one better prepare to talk about their invention and other related inventions with a professional patent attorney. In addition, the attorney will not spend too much time or money on patenting basics.