Mobile video applications have started to dominate the global mobile data traffic in recent years, and both opportunities and challenges have arisen when the emerging mobile cloud paradigm is introduced to support the resource-demanding video processing and networking services. This chapter offers in-depth discussions for contentand context-aware, adaptive, robust, secure, and real-time video a...

Everyday an enormous amount of video is captured by surveillance system for various purposes around the whole world. However, this is almost impossible for human to analyze the vast majority of video data. In this paper, a video summarization method is introduced combining foreground object, motion, and visual attention cue. Foreground objects typically provide important information about video...

360° video requires human viewers to actively control “where” to look while watching the video. Although it provides a more immersive experience of the visual content, it also introduces additional burden for viewers; awkward interfaces to navigate the video lead to suboptimal viewing experiences. Virtual cinematography is an appealing direction to remedy these problems, but conventional method...

Analytical Rate-Distortion-Complexity Modeling of Wavelet-based Scalable Video Coders Brian Foo,Yiannis Andreopoulos, and Mihaela van der Schaar Abstract Analytical modeling of the performance of video coders is essential in a variety of applications, such as power constrained processing, complexity-driven video streaming, etc., where information concerning rate, distortion or complexity (and t...

In this paper we present a novel object based video coder. This coder is based on an analysis-synthesis approach which allows for decoupling shape, motion and texture informations. These informations are then coded using wavelets decomposition and progressive coding allowing to have full scalability (object, SNR, temporal, and bitstream scalabilities). Experimental results show the benefits of ...

We present a method to perform video mosaicing for endomicroscopy with two major improvements compared to the state of the art. First, instead of using individual images directly, we start by creating sub-mosaics from short video sub-sequences using iconic registration. The sub-mosaics are then considered for feature-based registration. Second, groupwise estimation is performed between all subm...

Fully convolutional neural networks (FCNNs) trained on a large number of images with strong pixel-level annotations have become the new state of the art for the semantic segmentation task. While there have been recent attempts to learn FCNNs from image-level weak annotations, they need additional constraints, such as the size of an object, to obtain reasonable performance. To address this issue...

Video art has earned its spot within cultural heritage since the beginning of 1970s, especially as a medium for activist practices, and it is now one most collected exhibited artistic typologies in museums. The use video means social protest reflection continues to produce relevant artworks present day that constitute part our collective memory need be safeguarded future, they act valuable expr...