Jenny Benois-Pineau

DETECTION OF HUMAN FACES IN COLOR IMAGE SEQUENCES WITH ARBITRARY MOTIONS FOR VERY LOW BIT-RATE VIDEOPHONE CODING

Abstract The problem of human face detection is a focus of interest in image analysis, image databases and video coding. A new multi-resolution method using color and motion information and shape model is developed to detect human faces in videophone QCIF sequences for efficient encoding. The method is based on color segmentation and multiresolution propagation of a geometrical model. A new measure of motion activity is proposed to validate the choice of candidates.

Scene similarity measure for video content segmentation in the framework of a rough indexing paradigm

This article presents a scene similarity measure for video content segmentation. In the context of the rough indexing paradigm, we extract only partial information from MPEG compressed streams to measure the similarity of video frames through time. The similarity measure of I‐Frames is defined based on motion compensation of DC images and local contrast computation. The method allows a real‐time segmentation of the video content.

Extraction of foreground objects from an MPEG2 video stream in rough-indexing framework

In the domain of video indexing, one of the research topics is the automatic extraction of information to reach the objective of automatically describing and organizing the content. Thinking of a video stream, different kinds of information can be taken into account, but we can suppose that most of the information is contained in the foreground objects so that number of objects, their shape, their contours and so on, can constitute a good guess for the content description. This paper describes a new approach to extract foreground objects in MPEG2 video stream, in the framework of rough indexing paradigm we define. This paradigm leads us to reach the purpose in near real time, nevertheless maintaining a good level of details.

Object-Based Indexing of Compressed Video Content: From SD to HD Video

In the vast domain of digital multimedia libraries, the efficient and universal access to the stored data becomes possible due to content description and indexing metadata. Their automatic production is a challenging task addressing classical problems of objects extraction and description. In this framework, ever growing quantity of content is already available in compressed form. This holds for SD video encoded in MPEG standards and for quickly coming HD video for which recent standards as MJPEG2000 are used. In this paper we propose a general framework for efficient extraction of moving objects in SD and HD video with a focus on the hierarchical video signal representation by wavelets pyramids.

Dominant motion estimation and video partitioning with a 1D signal approach

This paper presents a novel approach for an automatic partitioning of video sequences based on scene change detection and global motion estimation. The method is based on a 1D representation of images, the Bin transform, which is a discrete version of the Radon transform. Analysis of the motion and detection of the scene change are realized in the transform domain using online statistical techniques. The analysis of a 1D signal rather than the mostly used 2D image signal limits computational complexity by itself and permits fast algorithms.

No-reference video quality assessment of H.264 video streams based on semantic saliency maps

The paper contributes to No-Reference video quality assessment of broadcasted HD video over IP networks and DVB. In this work we have enhanced our bottom-up spatio-temporal saliency map model by considering semantics of the visual scene. Thus we propose a new saliency map model based on face detection that we called semantic saliency map. A new fusion method has been proposed to merge the bottom-up saliency maps with the semantic saliency map. We show that our NR metric WMBER weighted by the spatio-temporal-semantic saliency map provides higher results then the WMBER weighted by the bottom-up spatio-temporal saliency map. Tests are performed on two H.264/AVC video databases for video quality assessment over lossy networks.

Region-based representation of video sequences with uniform background motion for a content-based image coding

Content-based image coders become the center of attention now for the currently emerging standard MPEG-4. A method based on the spatio-temporal segmentation for motion image coding is developed in this paper. The method is designed for the sequences characterized by homogeneous global motion (camera motion) and the presence of semantic objects having proper motions. The property of the method is the fitness of the moving border to spatial contours of regions which allows for a high quality of predicted images without any error encoding.

Intuitive color-based visualization of multimedia content as large graphs

Data visualization techniques are penetrating in various technological areas. In the field of multimedia such as information search and retrieval in multimedia archives, or digital media production and post-production, data visualization methodologies based on large graphs give an exciting alternative to conventional storyboard visualization. In this paper we develop a new approach to visualization of multimedia (video) documents based both on large graph clustering and preliminary video segmenting and indexing.

Human detection and tracking for video surveillance applications in a low-density environment

In this paper, we describe a new way to create an object oriented video surveillance system that monitors activity in a site. The process is performed in two steps: first, detection of human faces as a guess for objects of interest is done and tracking of these entities through a video stream. The guidelines here are not to perform a very accurate detection and tracking, based on the contours for example, but to provide a global image processing system on a simple Personal Computer taking advantage from co-operation of detection and tracking. So the scheme we propose here provides a simple, fast solution that tracks few specific points of interest on the object boundary and possibly engage a motion based detection in order to recover the object of interest in the scene or to detect new object of interest as well. This tracker also enables learning motion activities, detecting unusual activities, and supplying statistical information about motion in a scene.

Coding of structure in the region-based coder as a problem of optimization on graphs

This paper deals with the coding of structure in region-based coders for moving sequences of images. The sequence of images is represented as spatio-temporal map of regions homogeneous regarded to motion-based criterion and characterized by their shape model, topological relations and motion parameters. Topological and geometrical models of spatio-temporal segmentation are introduced. The coding of geometrical information is formulated as the problem of the construction of the Eulerian circuit in planar non-connected graph. A suboptimal algorithm is proposed. Some results for teleconference sequence are given.