: Here propose a new video inpainting method which applies to both static or free-moving camera videos. The method can be used for object removal, error concealment, and background reconstruction applications. To limit the computational time, a frame is inpainted by considering a small number of neighboring pictures which are grouped into a group of pictures (GoP). More specifically, to inpaint...

Removal of dynamic scene elements from video is an extremely challenging problem that even movie professionals often solve through days of manual frame-byframe editing. The disoccluded regions in the video have to be inpainted in a coherent way, even if originally occluded objects or background are dynamic. To make this problem easier, we propose a new approach for video inpainting that can dea...

A video logo is usually a declaration of the video copyright. However it sometimes causes visual discomfort due to the presence of multiple logos in videos that have been filed and exchanged by different channels. In this paper, we present an approach to erase logos from video clips. Based on the histogram energy analysis of the relevant video frames, we obtain the best quality logo frame that ...

This paper presents a general framework to adapt the size of a sport team video extracted from TV to a small device screen. We use a soccer game context to describe the four main steps of our video processing framework: (1) A view type detector helps to decide whether the current frame of the video has to be resized or not. (2) If the camera point of view is far, a ball detector localizes the i...

This work presents a procedure for refining depth maps acquired using RGB-D (depth) cameras. With numerous new structured-light RGB-D cameras, acquiring high-resolution depth maps has become easy. However, there are problems such as undesired occlusion, inaccurate depth values, and temporal variation of pixel values when using these cameras. In this paper, a proposed method based on an exemplar...

In the last decades, a large diversity of automatic, semi-automatic and manual approaches for video segmentation and knowledge extraction from video-data has been proposed. Due to the high complexity in both the spatial and temporal domain, it continues to be a challenging research area. In order to develop, train, and evaluate new algorithms, ground truth of video-data is crucial. Pixel-wise a...

Contemporary benchmark methods for image inpainting are based on deep generative models and specifically leverage adversarial loss for yielding realistic reconstructions. However, these models cannot be directly applied on image/video sequences because of an intrinsic drawbackthe reconstructions might be independently realistic, but, when visualized as a sequence, often lacks fidelity to the or...

In this report we investigate the application of texture synthesis and image inpainting techniques for video compression. Working in the non-parametric framework, we use 3D patches for matching and copying. This ensures temporal continuity to some extent which is not possible to obtain by working with individual frames. Since, in present application, patches might contain arbitrary shaped and m...