The detection of shot boundaries in video sequences is an important task for generating indexed video databases. This paper
provides a comprehensive quantitative comparison of the metrics that have been applied to shot boundary detection. In addition,
several standardized statistical tests that have not been applied to this problem, as well as three new metrics, are considered.
A mathematical framework for quantitatively comparing metrics is supplied. Experimental results based on a video database
containing 39,000 frames are included. 相似文献
The problem of channel sharing by rate adaptive streams belonging to various classes is considered. Rate adaptation provides
the opportunity for accepting more connections by adapting the bandwidth of connections that are already in the system. However,
bandwidth adaptation must be employed in a careful manner in order to ensure that (a) bandwidth is allocated to various classes
in a fair manner (system perspective) and (b) bandwidth adaptation does not affect adversely the perceived user quality of
the connection (user quality). The system perspective aspect has been studied earlier. This paper focuses on the equally important
user perspective. It is proposed to quantify user Quality of Service (QoS) through measures capturing short and long-term
bandwidth fluctuations that can be implemented with the mechanisms of traffic regulators, widely used in networking for the
purpose of controlling the traffic entering or exiting a network node. Furthermore, it is indicated how to integrate the user
perspective metrics with the optimal algorithms for system performance metrics developed earlier by the authors. Simulation
results illustrate the effectiveness of the proposed framework.
Leonidas GeorgiadisEmail:
Nikos G. Argiriou
received the Diploma degree in Electrical Engineering from the Department of Electrical Engineering, Telecommunication Division,
Aristotle University of Thessaloniki, Greece, in 1996. He worked as a researcher, on secure medical image transmission over
networks, at the Image Processing Lab at the same university during 1996–1997. During 1998–2000 he was a researcher for the
European Project Esprit Catserver concerning the use of advanced Quality of Service techniques in CATV networks. He received
his Ph.D. degree at Aristotle University of Thessaloniki in 2007. His current research interests are in the development and
implementation of QoS techniques for wired and wireless networks.
Leonidas Georgiadis
received the Diploma degree in Electrical Engineering from Aristotle University, Thessaloniki, Greece, in 1979, and his M.S.
and Ph.D degrees both in Electrical Engineering from the University of Connecticut, in 1981 and 1986, respectively. From 1986
to 1987 he was Research Assistant Professor at the University of Virginia, Charlottesville. In 1987 he joined IBM T. J. Watson
Research Center, Yorktown Heights as a Research Staff Member. Since October 1995, he has been with the Telecommunications
Department of Aristotle University, Thessaloniki, Greece. His interests are in the area of wireless networks, high speed networks,
routing, scheduling, congestion control, modeling and performance analysis. 相似文献
In the paper, we try to find a method that can service more users in a video-on-demand (VoD) system, based on MPEG-4 object
streams. The characteristics of object segmentation made on MPEG-4 videos can be utilized to reduce re-transmission of the
same objects, and then the saved bandwidth can be used to service more users. However, some thresholds must be analyzed first
to maintain the acceptable quality of services (QoS) requested by users, when reducing unnecessary object transmission on
one side. Thus, according to the defined thresholds, we propose a dynamically adjusting algorithm to coordinate the object
streams between the server and clients. The server not only allocates network bandwidth, but also adjusts ever-allocated QoS
appropriately using a degrading and upgrading strategy, based on the current network status. Lastly, through the simulation,
we found that our method has better performance than the other three methods owing to its flexibility to the network status.
A video encryption scheme combining with advanced video coding (AVC) is presented and analyzed in this paper, which is different
from the ones used in MPEG1/2 video encryption. In the proposed scheme, the intra-prediction mode and motion vector difference
are encrypted with the length-kept encryption algorithm (LKE) in order to keep the format compliance, and the residue data
of the macroblocks are encrypted with the residue data encryption algorithm (RDE) in order to keep low cost. Additionally,
a key distribution scheme is proposed to keep the robustness to transmission errors, which assigns sub-keys to different frames
or slices independently. The encryption scheme’s security, time efficiency and error robustness are analyzed in detail. Experimental
results show that the encryption scheme keeps file format unchanged, is secure against replacement attacks, is efficient in
computing, and is robust to some transmission errors. These properties make it a suitable choice for real-time applications,
such as secure IPTV, secure videoconference or mobile/wireless multimedia, etc.
This paper addresses the problem of estimating the 3D trajectory and associated uncertainty of an underwater autonomous vehicle from a set of images of the seabed taken by an onboard camera. The presented algorithms resort to the use of video mosaics and build upon previous work on image registration and visual pose estimation. The pose estimation is accomplished in two steps. Firstly, a video mosaic is created automatically, covering a region of interest of the seabed. Then, after associating a 3D referential for the mosaic, the estimation of the camera position from a new view of the scene becomes possible.
The main contribution of this paper lies on the assessment of the performance of the 3D pose algorithms. In order to do this, an image sequence with available ground-truth is used for precise error measuring. A first-order error propagation analysis is presented, relating the uncertainty in the location of the match points with the uncertainty in the pose parameters. The importance of predicting the estimate uncertainty is emphasized by the fact that it can be used for comparing algorithms and for the on-line monitoring of the vehicle trajectory reconstruction quality.
Several iterative and non-iterative pose estimation methods are discussed, differing both on the criteria being minimized and on the required information about the camera intrinsic parameters. This information ranges from the full knowledge of the parameters, to the case where they are estimated using self-calibration from an image sequence under pure rotation. The implemented pose algorithms are compared for the accuracy and estimate covariance. 相似文献