Digital Make up Face Generation

-

Digital Make up Face Generation





Goal

 Current make-up applications rely on using photoshop tools to apply makeup on the target's digital faces and generate results. While these applications allow customization, a customer who wants to quickly decide on the type of makeup kit to buy at a store will not find it useful. The customer might just want to find out how the make-up look on the cover or billboard will look like on her face. The goal of this project is to use an existing reference image of another subject with a make-up applied, and transfer the reference's make up on the target's face. The application can be further extended to photo retouching and illumination transfer from the reference image to the target.

 Methodology

 In order to transfer the make-up from the reference onto target in a pixel by pixel basis, the areas of interest must align. Face features such as eyes, nose, mouth and contours of the face, will be recognized using Active Shape Model (ASM) [1]. The features will then be aligned using Thin Plate Spline warping as proposed in [5]. Once the images are aligned, they will decomposed into lightness layer and color layer in CIELab color space by using weighted least square (WLS) filter[2]. The lightness layer will be further decomposed into large scale layer which include the largest changes in highlights due to make up and small scale layer which is not part of applied makeup areas. The transfer method of make up in the large scale layer will be transferred using gradient based methods [3]. Small scale layer of the target can be simply added in the final result. Finally, the color layer can be transferred through alpha blending.
It will be assumed that both the reference and the target have similar type of lighting conditions. This ensures that all the highlights are due to make up. Both images will face straight and upright with eyes open and mouths closed so that algorithms on Active Shape Model can be used successfully.

 References

 [1] S. Milborrow and F. Nicolls, "Locating Facial features with an Extended Active Shape Model," in EECV, 2008.
[2] Z. e. a. Farbman, "Edge-preserving decompositions for multi-scale tone and detail
manipulation," ACM Transactions on Graphics (TOG), vol. 27, no. 3, p. 67, 2008.
[3] X. Chen and e. al., "Face illumination transfer through edge-preserving filters," in Computer Vision and Pattern Recognition (CVPR), 2011.

 DOWNLOAD SOURCE CODE CLICK HERE 


Comments

Post a Comment

Popular posts from this blog

Light Field Images for Background Removal

-
Image
Light Field Images for Background Removal OUTPUT OVERVIEW Standard edge detection or foreground/background separation techniques, such as Otzu’smethod, require color or intensity differences between the background and regions that need tobe separated. For example, green screens are routinely set up as the background in a scene so thatthere is a clear difference in color between the background and foreground.Light filed images, captured in 4D and passively containing depth information for thescene can be used to approximate this effect. Depth estimation in the scene alone could provide a metric to separate the foreground and background, but more sophisticated methods are available.Considering the edge detection from a single image from a single viewpoint and analyzing the depths from the light field around the edges in that image, occluded edges and intensity or color edges can be distinguished. Along with the rest of the depth information this can allow the foreground and b
Read more

Using Image Processing to Identify and Score Darts thrown into a Dartboard

-
Image
✔️Using Image Processing to Identify and Score Darts thrown into a Dartboard ✔️Introduction The game of darts is a throwing sport in which participants toss projectiles into a circular target  attached to a vertical surface. The target is divided into many regions which correspond to different point and multiplier values. Darts is commonly played across North America and Europe and is a popular past time for many so an application that allows players to more conveniently keep score would be widely  beneficial. “Darts” is a general term for a targeting game following this basic premise and many game variations exist within this archetype; all utilizing the standard dart projectiles with a regulation dart board. Each game variant may have different objectives for which players to aim but identifying the region in  which the dart has hit in the dartboard is necessary for proper scoring. This project proposes the use of image processing to identify thrown darts and to det
Read more

aerodynamic performance

-
Image
✔️   AERODYNAMIC PERFORMANCE DURING FLAPPING FLIGHT ✔️   Background and Motivation Quantifying the aerodynamic performance of freely flying birds is an open challenge in the field, because it is inherently difficult to directly measure the forces generated and the power required by flapping wings without impeding their natural motion. Force estimates are thus frequently derived from kinematic analysis of high speed video. Acquiring this data has traditionally involved tracking markers on the bird, as in [1], using software tools, such as the DLT program described in [2]. Although this program has some automatic tracking capabilities, they only work well with very clearly visible markers and relatively uncluttered backgrounds. However, artificial markers may interfere with the flight of smaller birds. Natural landmarks, such as the eye of the bird, can be
Read more