|Place of Conferral||中国科学院自动化研究所|
|Keyword||图像取证 光照分析 人脸图像 光照估计 透视投影 活体检测|
1.人脸上复杂阴影、重建人脸模型的误差会严重影响现有光照估计方法的准确性。本文利用阴影客观反映环境光照的物理事实，提出了基于环境光/漫反射光分离的光照估计方法（Light Estimation based on Ambient/Diﬀuse light separation，LEAD）。首先提出一种更符合物理事实的环境光/漫反射光分离的球面谐波光照模型（Sphere Harmonic lighting based on Ambient/Diﬀuse light separation，SHAD）。在此基础上，利用迭代的方法估计环境光照，进而估计漫反射光照。实验表明，相比于现有的光照估计算法，本文方法增强了光照估计对于毛发纹理、复杂阴影、以及法向量误差等因素的鲁棒性。利用该方法得到的光照，结合环境光等信息进行光照一致性判断，可以得到更加符合客观实际、更令人信服的判断意见。
With the popularity of cameras, mobile phones and the Internet, as well as the continuous development of video editing tools and video processing technologies, people can easily modify the images, which brings convenience to life. But it also raises doubts about the authenticity of the images. In particular, placing a person’s face into another photo or a piece of video, creating the illusion that the person is involved in the event presented by the image, is the most common and harmful type of malicious tampering. Recently, face-related security issues have attracted widespread attention due to the bad events caused by the attack of face photos/video on the ride-hailing client’s face veriﬁcation and alipay’s face payment. Therefore, it is of great signiﬁcance to study the forensics technology of face image authenticity.
Previous researches on image forensics focusing on digital authenticity, content authenticity and object authenticity, have made certain achievement. However, all of them have speciﬁc conditions and scope of application, and are easily attacked by anti-forensics. In practical applications, it’s very common that a variety of forensic methods are needed to give valid appraisal opinions. As an essential element of imaging, illumination has been widely studied and applied in image forensics. But there are still many places worthy of further exploration, improvement and ﬂexible application. Therefore, the research objective of this paper is to study the face image forensics method based on illumination analysis, so as to obtain the methods with higher accuracy, better robustness and stronger persuasiveness, and apply them in practical problems.
The main research contents and innovations of this paper have the following three points: 1.The complex shadows on the human face and the error in the reconstructed face model can seriously aﬀect the accuracy of existing illumination estimation methods. In this paper, a method of illumination estimation based on ambient light/diﬀuse light separation (LEAD) is proposed by using the physical fact that shadows reﬂect ambient light conditions objectively. Firstly, we propose a sphere harmonic lighting based on ambient/diﬀuse light separation (SHAD) which is more in line with physical facts. On this basis, the iterative method is employed to estimate ambient illumination and diﬀuse illumination. Experimental results show that compared with the existing illumination estimation methods, our proposed method enhances the robustness of illumination estimation for hair texture, complex shadows, and normal vector errors. The illumination obtained by this method, combined with the ambient light and other information for the illumination consistency judgment, oﬀers more objective and convincing judgment opinions for image forensics. 2.The traditional method estimate the illumination based on the parallel projection and weak perspective projection, which deviates from the fact that the camera model is a perspective model. As a result, the direct comparison of consistency analysis using these methods will bring inherent errors. This paper presents a spatial illumination estimation algorithm under perspective projection. By unifying the coordinate system of each object into the camera coordinate system, the spatial illumination of each object relative to the camera coordinate system is obtained, and the accuracy of the illumination estimation method is signiﬁcantly improved from the physical principle. Experimental results show that compared with the traditional illumination consistency analysis based on parallel projection illumination, the spatial illumination obtained by this method has higher accuracy. What’s more, combing with the equivalent focal length, space face location, re-projected image and other related information for photo space rationality analysis, we can get a more convincing conclusion. 3. According to the fact that the they are under the umbrella of photos and screens, the spooﬁng faces are unable to respond to changes in external illumination, while illumination distribution of the real faces changes with illumination, this paper proposes a face spooﬁng detection method based on illumination change analysis to identify real faces and spooﬁng faces by calculating the correlation of illumination changes of face and scene before and after external illumination changes. Through the steps of light estimation, changing illumination, calculating correlation, and hypothesis testing judgment, it is eﬀectively perform face spooﬁng judgment. Experimental results show the eﬀectiveness of proposed method on multiple kinds of face attacks including printed photo, screen photo, and video replay attack, and other advantages such as user cooperation free, loose using conditions, simple equipment demand, easy to camouﬂage and propitious to face recognition.
|张旭. 基于光照分析的人脸图像取证算法研究[D]. 中国科学院自动化研究所. 中国科学院自动化研究所,2019.|
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