A novel filter for block-based motion estimation

Noises, in the form of false motion vectors, cannot be avoided while capturing block motion vectors using block based motion estimation techniques. Similar noises are further introduced when the technique of global motion compensation is applied to obtain 'true' object motion from video sequences, where both the camera and object motions are present. We observe that the performance of the mean and the median filters in removing false motion vectors, for estimating 'true' object motion, is not satisfactory, especially when the size of the object is significantly smaller than the scene. In this paper we introduce a novel filter, named as the Mean-Accumulated-Thresholded (MAT) filter, in order to capture 'true' object motion vectors from video sequences with or without the camera motion (zoom and/or pan). Experimental results on representative standard video sequences are included to establish the superiority of our filter compared with the traditional median and mean filters

A video object generation tool allowing friendly user interaction

In this paper we describe an interactive video object segmentation tool developed in the framework of the ACTS-AC098 MOMUSYS project. The Video Object Generator with User Environment (VOGUE) combines three different sets of automatic and semi-automatic-tool (spatial segmentation, object tracking and temporal segmentation) with general purpose tools for user interaction. The result is an integrated environment allowing the user-assisted segmentation of any sort of video sequences in a friendly and efficient manner.Peer ReviewedPostprint (published version

Interaction between high-level and low-level image analysis for semantic video object extraction

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Segmentation and tracking of video objects for a content-based video indexing context

This paper examines the problem of segmentation and tracking of video objects for content-based information retrieval. Segmentation and tracking of video objects plays an important role in index creation and user request definition steps. The object is initially selected using a semi-automatic approach. For this purpose, a user-based selection is required to define roughly the object to be tracked. In this paper, we propose two different methods to allow an accurate contour definition from the user selection. The first one is based on an active contour model which progressively refines the selection by fitting the natural edges of the object while the second used a binary partition tree with aPeer ReviewedPostprint (published version

Video object segmentation introducing depth and motion information

We present a method to estimate the relative depth between objects in scenes of video sequences. The information for the estimation of the relative depth is obtained from the overlapping produced between objects when there is relative motion as well as from motion coherence between neighbouring regions. A relaxation labelling algorithm is used to solve conflicts and assign every region to a depth level. The depth estimation is used in a segmentation scheme which uses grey level information to produce a first segmentation. Regions of this partition are merged on the basis of their depth level.Peer ReviewedPostprint (published version

Region-based representations of image and video: segmentation tools for multimedia services

This paper discusses region-based representations of image and video that are useful for multimedia services such as those supported by the MPEG-4 and MPEG-7 standards. Classical tools related to the generation of the region-based representations are discussed. After a description of the main processing steps and the corresponding choices in terms of feature spaces, decision spaces, and decision algorithms, the state of the art in segmentation is reviewed. Mainly tools useful in the context of the MPEG-4 and MPEG-7 standards are discussed. The review is structured around the strategies used by the algorithms (transition based or homogeneity based) and the decision spaces (spatial, spatio-temporal, and temporal). The second part of this paper proposes a partition tree representation of images and introduces a processing strategy that involves a similarity estimation step followed by a partition creation step. This strategy tries to find a compromise between what can be done in a systematic and universal way and what has to be application dependent. It is shown in particular how a single partition tree created with an extremely simple similarity feature can support a large number of segmentation applications: spatial segmentation, motion estimation, region-based coding, semantic object extraction, and region-based retrieval.Peer ReviewedPostprint (published version

Fast algorithm for the 3-D DCT-II

Recently, many applications for three-dimensional (3-D) image and video compression have been proposed using 3-D discrete cosine transforms (3-D DCTs). Among different types of DCTs, the type-II DCT (DCT-II) is the most used. In order to use the 3-D DCTs in practical applications, fast 3-D algorithms are essential. Therefore, in this paper, the 3-D vector-radix decimation-in-frequency (3-D VR DIF) algorithm that calculates the 3-D DCT-II directly is introduced. The mathematical analysis and the implementation of the developed algorithm are presented, showing that this algorithm possesses a regular structure, can be implemented in-place for efficient use of memory, and is faster than the conventional row-column-frame (RCF) approach. Furthermore, an application of 3-D video compression-based 3-D DCT-II is implemented using the 3-D new algorithm. This has led to a substantial speed improvement for 3-D DCT-II-based compression systems and proved the validity of the developed algorithm

Real-Time Rough Extraction of Foreground Objects in MPEG1,2 Compressed Video

This paper describes a new approach to extract foreground objects in MPEG1,2 video streams, in the framework of “rough indexing paradigm”, that is starting from rough data obtained by only partially decoding the compressed stream. In this approach we use both P-frame motion information and I-frame colour information to identify and extract foreground objects. The particularity of our approach with regards to the state of the art methods consists in a robust estimation of camera motion and its use for localisation of real objects and filtering of parasite zones. Secondly, a spatio-temporal filtering of roughly segmented objects at DC resolution is fulfilled using motion trajectory and gaussian-like shape characteristic function. This paradigm results in content description in real time, maintaining a good level of details

An approach to summarize video data in compressed domain

Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2007Includes bibliographical references (leaves: 54-56)Text in English; Abstract: Turkish and Englishx, 59 leavesThe requirements to represent digital video and images efficiently and feasibly have collected great efforts on research, development and standardization over past 20 years. These efforts targeted a vast area of applications such as video on demand, digital TV/HDTV broadcasting, multimedia video databases, surveillance applications etc. Moreover, the applications demand more efficient collections of algorithms to enable lower bit rate levels, with acceptable quality depending on application requirements. In our time, most of the video content either stored, transmitted is in compressed form. The increase in the amount of video data that is being shared attracted interest of researchers on the interrelated problems of video summarization, indexing and abstraction. In this study, the scene cut detection in emerging ISO/ITU H264/AVC coded bit stream is realized by extracting spatio-temporal prediction information directly in the compressed domain. The syntax and semantics, parsing and decoding processes of ISO/ITU H264/AVC bit-stream is analyzed to detect scene information. Various video test data is constructed using Joint Video Team.s test model JM encoder, and implementations are made on JM decoder. The output of the study is the scene information to address video summarization, skimming, indexing applications that use the new generation ISO/ITU H264/AVC video