In order to reduce the computational complexity, most of the video classification approaches
represent video data at frame level. In this paper we investigate a novel perspective that …

The increasing amount of digital multimedia content available is inspiring potential new
types of user interaction with video data. Users want to easily find the content by searching …

With the recent revolution in the field of multimedia technology, video data have become
much easier and straightforward to be created, stored and transferred on a huge scale with …

In video global features are often used for reasons of computational efficiency, where each
global feature captures information of a single video frame. But frames in video change over …

The production of video has increased and expanded dramatically. There is a need to reach
accurate video classification. In our work, we use deep learning as a mean to accelerate the …

In this paper we propose an in-depth evaluation of the performance of video descriptors to
multimodal video genre categorization. We discuss the perspective of designing appropriate …

In this paper we introduce a new video description framework that replaces traditional Bag-
of-Words with a combination of Fisher Kernels (FK) and Vector of Locally Aggregated …

In this paper, we investigate multi-modal approaches to retrieve associated news stories
sharing the same main topic. In the visual domain, we employ near duplicate …

Video content has a pronounced and varied cognitive impact. This thesis develops several
statistical models of video and demonstrates that these models can be used as a means of …

La forte augmentation du volume de données multimédia impose la mise au point de
solutions adaptées pour une exploration visuelle efficace des bases multimédia. Après avoir …