Photo Response Non-Uniformity (PRNU) based source camera attribution is an effective method to determine an image or a video’s origin camera. However, modern devices, especially smartphones, capture images and videos at different resolutions using the same sensor array, PRNU attribution can become ineffective as the camera fingerprint and query object can be misaligned. While capturing visual objects (either image or video), cameras may use different in-camera operations as well as they may use different parts of the sensor. In this paper, we investigate the problem of source camera attribution of a visual object by doing a thorough investigation of a comprehensive dataset, NYUAD Mixed Media Dataset. This investigation takes many factors into accounts, such as the fact that visual objects may have been captured using different resolution and aspect ratios. Furthermore, the visual objects may use different regions of the sensor, including the usage of boundary pixels for videos. Taking these various cases into account, we propose an efficient search which not only gives the state-of-the-art results but also performs significantly faster compared to existing methods.

基于光响应非均匀性（PRNU）的源摄像机归属是确定图像或视频源摄像机的有效方法。但是，现代设备（尤其是智能手机）使用相同的传感器阵列捕获不同分辨率的图像和视频，由于相机指纹和查询对象可能未对齐，PRNU归因可能变得无效。在捕获视觉对象（图像或视频）时，相机可能会使用不同的相机内操作，并且可能会使用传感器的不同部分。在本文中，我们通过对综合数据集NYUAD混合媒体数据集进行全面研究，调查了视觉对象的源摄像机属性问题。这项调查考虑了许多因素，例如视觉对象可能已使用不同的分辨率和宽高比捕获的事实。此外，视觉对象可以使用传感器的不同区域，包括使用视频的边界像素。考虑到这些各种情况，我们提出了一种有效的搜索方法，该方法不仅可以提供最新的结果，而且与现有方法相比，其执行速度也快得多。