Assessing human skin color from uncalibrated images

Images of a scene captured with multiple cameras will have different color values due to variations in color rendering across devices. We present a method to accurately retrieve color information from uncalibrated images taken under uncontrolled lighting conditions with an unknown device and no access to raw data, but with a limited number of reference colors in the scene. The method is used to assess skin tones. A subject is imaged with the calibration target in the scene. This target is extracted and its color values are used to compute a color correction transform that is applied to the entire image. We establish that the best mapping is done using a target consisting of skin colored patches representing the whole range of human skin colors. We show that color information extracted from images is well correlated with color data derived from spectral measurements of skin. We also show that skin color can be consistently measured across cameras with different color rendering and resolutions ranging from 0.1 Mpixels to 4.0 Mpixels

Skin texture and colour predict perceived health in Asian faces

Facial skin texture and colour play an important role in observers' judgments of apparent health and have been linked to aspects of physiological health, including fitness, immunity and fertility. However, most studies have focused on Caucasian populations. Here, we report two studies that investigate the contribution of skin texture and colour to the apparent health ofMalaysian Chinese faces. In Study 1, homogenous skin texture, as measured by wavelet analysis, was found to positively predict ratings of apparent health of Asian faces. In study 2, homogenous skin texture and increased skin yellowness positively predicted rated health of Malaysian Chinese faces. This finding suggests that skin condition serves as an important cue for subjective judgements of health in Malaysian Chinese faces

Facial Skin Coloration Affects Perceived Health of Human Faces

Numerous researchers have examined the effects of skin condition, including texture and color, on the perception of health, age, and attractiveness in human faces. They have focused on facial color distribution, homogeneity of pigmentation, or skin quality. We here investigate the role of overall skin color in determining perceptions of health from faces by allowing participants to manipulate the skin portions of color-calibrated Caucasian face photographs along CIELab color axes. To enhance healthy appearance, participants increased skin redness (a*), providing additional support for previous findings that skin blood color enhances the healthy appearance of faces. Participants also increased skin yellowness (b*) and lightness (L*), suggesting a role for high carotenoid and low melanin coloration in the healthy appearance of faces. The color preferences described here resemble the red and yellow color cues to health displayed by many species of nonhuman animals

3D SCANNING AND CHARACTERIZATION OF SKIN LESIONS

Skin lesions, including burn wounds, are characterized by several key physical properties including the size, shape, and coloration of the wound. Assessing the state of the wound is critical to ensure the best chance of patient recovery. Initial assessments are typically done with visual inspection, which, given human eyes, is subjective and non-repeatable. In this study, we investigated the feasibility of characterizing skin wound properties, such as surface area, based on the 3D model obtained with an iOS device, aiming for providing more accurate skin wound assessment than conventional 2D imaging based assessment. Since 2D images lack depth data, they cannot be used to characterize variable heights across a wound, and they would not be able to account for curved or irregularly shaped body surfaces when calculating area. We achieved 3D scanning capability with an iOS device by repurposing its dot projector module, which is an essential component in the ‘Face ID’ function. We chose to use dot projector scanning over other existing 3D scanning methods, such as photometry, due to dot projection offering consistent scaling and faster scan speed. We developed a custom tool to accurately segment the affected skin regions in a scanned model based on user inputs and color data. Segmentation was accomplished by utilizing global color thresholding to objectively segregate damaged skin area from healthy tissues. Geometrical information such as surface area, heights of specific deformations, and perimeters of specific sections could be quantified. We determined that a 3D model with high accuracy can be obtained if the distance between the iPad and the object is less than 18 inches. Segmenting such models works consistently so long as the region is evenly lit and uniformly colored, though utilizing multistep segmentation can aid in varied colored regions. We conducted a calibration study on objects with known surface areas to minimize the discrepancy between the ground truth and the quantified values. Our results demonstrated that the error of the calibrated results is within 5% and the variation is less than 3% when it was used to quantify objects with known flat surface areas. On the complex geometry of simulated skin burns, we found that the coefficient of variation was about 10% for multiple scans. Our study demonstrated that it is feasible to accurately characterize skin wounds using 3D models acquired with an iOS device. This technique can be applied in clinical settings to assess/document the severity of skin injury and track the recovery and response to the treatment. It also has the potential to facilitate telemedicine with high fidelity 3D imagery

3D Face Reconstruction: the Road to Forensics

3D face reconstruction algorithms from images and videos are applied to many fields, from plastic surgery to the entertainment sector, thanks to their advantageous features. However, when looking at forensic applications, 3D face reconstruction must observe strict requirements that still make its possible role in bringing evidence to a lawsuit unclear. An extensive investigation of the constraints, potential, and limits of its application in forensics is still missing. Shedding some light on this matter is the goal of the present survey, which starts by clarifying the relation between forensic applications and biometrics, with a focus on face recognition. Therefore, it provides an analysis of the achievements of 3D face reconstruction algorithms from surveillance videos and mugshot images and discusses the current obstacles that separate 3D face reconstruction from an active role in forensic applications. Finally, it examines the underlying data sets, with their advantages and limitations, while proposing alternatives that could substitute or complement them.Comment: The manuscript has been accepted for publication in ACM Computing Surveys. arXiv admin note: text overlap with arXiv:2303.1116

Imparting 3D representations to artificial intelligence for a full assessment of pressure injuries.

During recent decades, researches have shown great interest to machine learning techniques in order to extract meaningful information from the large amount of data being collected each day. Especially in the medical field, images play a significant role in the detection of several health issues. Hence, medical image analysis remarkably participates in the diagnosis process and it is considered a suitable environment to interact with the technology of intelligent systems. Deep Learning (DL) has recently captured the interest of researchers as it has proven to be efficient in detecting underlying features in the data and outperformed the classical machine learning methods. The main objective of this dissertation is to prove the efficiency of Deep Learning techniques in tackling one of the important health issues we are facing in our society, through medical imaging. Pressure injuries are a dermatology related health issue associated with increased morbidity and health care costs. Managing pressure injuries appropriately is increasingly important for all the professionals in wound care. Using 2D photographs and 3D meshes of these wounds, collected from collaborating hospitals, our mission is to create intelligent systems for a full non-intrusive assessment of these wounds. Five main tasks have been achieved in this study: a literature review of wound imaging methods using machine learning techniques, the classification and segmentation of the tissue types inside the pressure injury, the segmentation of these wounds and the design of an end-to-end system which measures all the necessary quantitative information from 3D meshes for an efficient assessment of PIs, and the integration of the assessment imaging techniques in a web-based application

3D Face Reconstruction: the Road to Forensics

3D face reconstruction algorithms from images and videos are applied to many fields, from plastic surgery to the entertainment sector, thanks to their advantageous features. However, when looking at forensic applications, 3D face reconstruction must observe strict requirements that still make its possible role in bringing evidence to a lawsuit unclear. An extensive investigation of the constraints, potential, and limits of its application in forensics is still missing. Shedding some light on this matter is the goal of the present survey, which starts by clarifying the relation between forensic applications and biometrics, with a focus on face recognition. Therefore, it provides an analysis of the achievements of 3D face reconstruction algorithms from surveillance videos and mugshot images and discusses the current obstacles that separate 3D face reconstruction from an active role in forensic applications. Finally, it examines the underlying data sets, with their advantages and limitations, while proposing alternatives that could substitute or complement them

Cell Phones as Imaging Sensors

Camera phones are ubiquitous, and consumers have been adopting them faster than any other technology in modern history. When connected to a network, though, they are capable of more than just picture taking: Suddenly, they gain access to the power of the cloud. We exploit this capability by providing a series of image-based personal advisory services. These are designed to work with any handset over any cellular carrier using commonly available Multimedia Messaging Service (MMS) and Short Message Service (SMS) features. Targeted at the unsophisticated consumer, these applications must be quick and easy to use, not requiring download capabilities or preplanning. Thus, all application processing occurs in the back-end system (i.e., as a cloud service) and not on the handset itself. Presenting an image to an advisory service in the cloud, a user receives information that can be acted upon immediately. Two of our examples involve color assessment – selecting cosmetics and home décor paint palettes; the third provides the ability to extract text from a scene. In the case of the color imaging applications, we have shown that our service rivals the advice quality of experts. The result of this capability is a new paradigm for mobile interactions — image-based information services exploiting the ubiquity of camera phones

3D Face Reconstruction for Forensic Recognition - A Survey

3D face reconstruction algorithms from images and videos are applied to many fields, from plastic surgery to the entertainment sector, thanks to their advantageous features. However, when looking at forensic applications, 3D face reconstruction must observe strict requirements that still make unclear its possible role in bringing evidence to a lawsuit. Shedding some light on this matter is the goal of the present survey, where we start by clarifying the relation between forensic applications and biometrics. To our knowledge, no previous work adopted this relation to make the point on the state of the art. Therefore, we analyzed the achievements of 3D face reconstruction algorithms from surveillance videos and mugshot images and discussed the current obstacles that separate 3D face reconstruction from an active role in forensic applications