nils-herrmann/clean_scirepeval huggingface dataset:
DAQ system for LEPS experiment

The DAQ system for the experiment with Laser Electron Photons at SPring-8 (LEPS) is developed based on the network distributed architecture. The system is designed so as to collect data from various front-end electronics in a 1 kHz trigger rate. In order to provide modularity, scalability and flexibility, local DAQ systems are made by attaching the VME board computers to the four front-ends. Data of the each local DAQ system are sent through Fast Ethernet to the data server. With this DAQ system, the /spl phi/ photo-production experiment at LEPS started on May 2000. Data are taken from scintillation counters, drift chambers and silicon strip detectors. The performance of the DAQ system is enough high for the measurement.
Fast and improved seam carving with strip partition and neighboring probability constraints

Seam carving is an effective way of image retargeting. However, existing seam carving schemes often come with unacceptable artifacts and are quite time consuming. In this paper, we propose a fast seam carving scheme with strip partition and neighboring probability constraints to resolve these two problems simultaneously. Firstly, we split the original image into several strips of equal space and we estimate the importance of each strip by its average saliency values. This partition results that more seams are removed from the strips consisting of more unimportant regions while fewer seams are removed from that of more important regions. Then, we establish the adjacency relationship by maximum correlation . The neighboring probability is obtained to describe the neighboring relationship between the seams. Finally, by combining the neighboring probability and their accumulated energy, least important seams are removed. The neighboring probability constraint ensures that the seam removal is distributed to avoid abrupt changes in the scene. This leads to an improved quality in the resized image. The experimental results show that the proposed approach performs better than the state-of-the-art seam carving schemes.
Epicardial motion and deformation estimation from coronary artery bifurcation points

A special problem in nonrigid motion analysis, the problem of estimating the motion and deformation of the human heart, is addressed. The research has been conducted on the left ventricle 3-D data of the bifurcation points, obtained within the period of one cardiac cycle. The process of the motion analysis is divided into three phases: global motion estimation, global motion compensation, and local deformation estimation. The global motion of the left ventricle is determined using the estimated principal axes over successive time instants. Upon compensation for the global motion, the local deformation is analyzed utilizing the correspondence of individual bifurcation points over the period of the cardiac cycle via tensor analysis. Finally, in order to better understand the complex nature of the left ventricle movement, several scientific visualization techniques are exploited to view the dynamic deformation of the left ventricle surface.<<ETX>>
User guided semantic image adaptation for mobile display devices

This paper proposes a novel semantics-based consumer photo adaptation scheme for users of small-display mobile devices. The main contributions of the proposed scheme are: 1) seamless integration of mobile user supplied semantic information with low level image features to identify se-mantically important regions-of-interest (ROI), and 2) perceptually optimized adaptation for photo display on mobile devices. In order to bridge the semantic gap in photo search in a consumer photo collection and to perform appropriate adaptation of perceptually important region-of-interest from each photo to fit small displays on the mobile devices, we design a Bayesian fusion approach to properly integrate low level features with high level semantics. Low level features are extracted in a bottom-up fashion while the high level semantics is applied in a top-down style. Extensive experiments have been carried out based on several common events defined in the Kodak consumer photo database. These experiments show that by utilizing the semantics provided by the mobile device users, perceptually consistent adaptation can be effectively carried out. This new semantic adaptation scheme is able to outperform the conventional attention-based scheme for the common events and produce desired regions for the small displays on mobile devices.
An improved approach for cardiac dynamics analysis based on constrained local force model [CT volumetric images]

Proposes a constrained local force model to estimate the non-rigid motion of left ventricle over a cardiac cycle. The local force model is derived from the dynamics of independent point masses driven by local constant forces over a short period of time. The trajectory that minimizes the kinetic energy required to move a point mass from one surface to another is considered as the local displacement vector. However, the original model suffers from problems of potential one-to-many point correspondence and inconsistent motion estimation. The proposed constrained local force model attempts to achieve better and more accurate motion estimation. First, Gaussian curvature is incorporated as constraint on point correspondence to solve the one-to-many correspondence problem. Second, motion estimations of neighboring points are taken into account to obtain more consistent estimation. Experimental results show that the constrained model achieves an improved estimation in cardiac motion analysis.
Editorial Message From the Outgoing Editor-in-Chief

M Y SECOND term as the Editor-in-Chief for TCSVT) completed at the end of 2009. It has been a great pleasure to serve two consecutive terms as the Editor-in-Chief for TCSVT for the past four years. The wonderful experiences working with IEEE publication staff members, associate editors, reviewers, authors, and readers have been the highlights of my professional career. Over the last four years, we have witnessed significant growth of TCSVT in several key areas. Among them, the most impressive ones are: 1) we have more than doubled the number of annual new paper submission from under 300 in 2005 to over 600 in 2009; and 2) we have nearly doubled the impact factor from 1.7 in 2006 to 2.95 in 2009. Other areas of growth for TCSVT include the expansion of scope to recruit papers from emerging areas of video technology and the publication of six special issues in the past three years, ranging from H.264 SVC to multiview video coding, and from 3DTV to algorithm and architecture coexploration. I am most indebted to the wonderful team of publication staff members, associate editors, and reviewers for their dedicated services to select and publish extremely high quality papers for publication in TCSVT. In particular, I would like to thank all associate editors who have answered my frequent calls to process the papers assigned to them in a timely fashion. I would also like to thank the authors for submitting their high quality papers to TCSVT and the readers for continued support to TCSVT by citing papers published in TCSVT. Without their continued and unselfish commitments, TCSVT would not have achieved its current premier status. His current research interests include reliable and secure multimedia streaming over P2P, wireless and ad hoc networks, mobile multimedia systems-processing and analysis for mobile systems and devices, medical image analysis and biomedical information processing, distributed source coding for distributed systems and digital signal processing for communications, collaborative signal processing, and data aggregation for sensor networks. He has also chaired and served in numerous technical program committees for IEEE, the Association for Computing Machinery, and other international conferences. He was elected a Fellow of the International Society for Optical Engineers for his contributions in electronic imaging and visual communications. Over the last four years, I was able to bring together a distinguished team of Associate Editors to professionally …
Energy efficient h.264 video transmission over wireless ad hoc networks based on adaptive 802.11e EDCA MAC protocol

This paper presents an energy efficient H.264 video transmission over wireless ad hoc networks based on an adaptive IEEE 802.11e EDCA (enhanced distributed channel access) mechanism. The standard IEEE 802.11e EDCA mechanism provides only service priority differentiation for time bound applications over ad hoc networks. However, this standard does not provide adaptation mechanism to respond to the time varying network link status. Furthermore, the critical issues in energy efficient transmission have not been addressed under EDCA mechanism. In this research we develop a new adaptive scheme to adjust the Contention Window (CW) after each transmission attempt based on current network link status. This adaptation scheme is also integrated with energy efficient FHSS (BFSK) scheme in order to save the energy consumption during the transmission. An analytical model of Energy efficient estimator (E3 metric) is developed to support the selection of modulation scheme. We also carry out NS-2 based simulation, in combination with E3 model, to evaluate the proposed scheme in comparison with standard IEEE 802.11e EDCA. Based on extensive simulation with H.264/AVC video over the proposed AEDCA and the standard EDCA, we demonstrate that the proposed AEDCA with Energy efficient BFSK scheme outperforms the standard IEEE 802.11e EDCA with an improved video quality as well as reduced energy dissipation.
A joint layered coding scheme for unified reliable and secure media transmission with implementation on JPEG 2000 images

This paper presents a novel stream-level joint layered coding scheme for unified reliable and secure media transmission over wireless networks. The proposed scheme simultaneously protects both compressed media content and the authentication data from wireless channel impairments. Therefore, the media quality degradation incurred by both channel noise and authentication constraints can be minimized. With a prior knowledge of source coding and channel coding, the proposed joint system integrates authentication into the media error protection components to ensure 100% effective verification probability, i.e. every source decodable media unit is authenticable. In particular, by utilizing the contextual relationship, such as coding dependency and content importance between media slices for authentication hash appending, the proposed scheme generates an extremely low authentication overhead. The proposed authentication scheme is fundamentally different from many existing systems that consider the problem of authenticating media content separately from the other operations in the media transmission system. Under this joint layered coding framework, an optimal rate allocation algorithm for source coding, channel coding and media authentication is developed to guarantee the end-to-end media quality. Experiment results on JPEG 2000 images validate the proposed scheme and demonstrate that the performance of the proposed approach is approaching its upper bound, in which case no authentication is applied to the media stream.
Distortion bounds for transmitting correlated sources with common part over MAC

This paper investigates the joint source-channel coding problem of sending two correlated memoryless sources with common part over a memoryless multiple access channel (MAC). An inner bound and two outer bounds on the achievable distortion region are derived. In particular, they respectively recover the existing bounds for several special cases, such as communication without common part, lossless communication, and noiseless communication. When specialized to quadratic Gaussian communication case, the inner bound and outer bound are used to generate two new bounds. Numerical result shows that common part improves the performance of such distributed communication system.
Compressive Coded Modulation for Seamless Rate Adaptation

This paper presents a novel compressive coded modulation (CCM) which simultaneously achieves joint source-channel coding and seamless rate adaptation. The embedding of source compression into modulation brings significant throughput gain when the physical layer data contain non-negligible redundancy. The kernel of CCM is a new random projection (RP) code inspired by the compressive sensing (CS) theory. The RP code generates multilevel symbols from source binaries through weighted sum operations. Then, the generated RP symbols are mapped into a dense constellation for transmission. The receiver performs joint decoding based on received symbols. As the number of RP symbols can be adjusted in fine granularity, the rate adaptation becomes seamless. Two key design issues in the proposed CCM are addressed in this paper. First, we consider the RP code design for sources with different redundancies. Three principles are established and a concrete implementation is given. Second, we devise a linear-time decoding algorithm for the proposed RP code. In this belief propagation (BP) algorithm, we find that computing convolution in time domain is more efficient than that in frequency domain for binary variable nodes. Moreover, we invent a ZigZag deconvolution to further reduce the complexity. Analysis show that the proposed decoding algorithm is nearly 20 times faster than the state-of-the-art BP algorithm for CS called CS-BP. Emulations on traced data show that CCM achieves significant throughput gain, up to 33% and 70%, respectively, over the Hybrid ARQ with compression and BICM with compression, under practical time-varying wireless channels.
Continuous Network Coding in Wireless Relay Networks

Network coding has recently been applied to wireless networks and has achieved some initial success. Researches in wireless network coding have been mostly focusing on utilizing the broadcast nature of the wireless networks. In this paper, we propose a novel network coding framework for wireless relay networks that also takes into consideration the fading and error prone nature of the wireless networks. First, we extend the traditional network coding in lossless networks which operates on 0-1 bits, to a new framework which defines network coding on the posterior probability of each bit. This new framework allows an imperfect decode-recode process at a relay node and avoids possible error propagation when a hard decision is made at the relay node. It implicitly integrates decode-and-forward and estimate-and-forward strategies for wireless network coding to address the technical issues of channel fading and transmission errors. The proposed approach is validated through both theoretical analysis and extensive simulations. Both analysis and simulation confirm that this new framework is able to achieve significant gain over traditional network coding. This new framework also enables the introduction of adaptive scheme into network coding. We demonstrate a basic adaptation scheme and present some preliminary experimental results. The proposed adaptive scheme will lay down an essential foundation in this emerging field of wireless network coding in order to address issues related to link heterogeneity.
Finding your spot: A photography suggestion system for placing human in the scene

Capturing a professional like photo is always a challenging task, especially for novice users. This paper proposes a photography suggestion approach to assist users to take high visual quality photos with human in the scene. In this research, we first investigate a set of aesthetic composition rules and visual perception principles to construct an aesthetic score prediction model in order to measure visual quality in terms of photo composition. Then we conduct a study on professional photos to define a proper size for the enclosure of human into the picture of a given scene. The proposed approach is able to leverage saliency and geometric detection to represent composition features. Finally, we utilize an efficient hierarchical search to obtain the optimal enclosure for human in the scene. Extensive experiments have been performed for hot spot landmark locations. Through subjective evaluation, the results show that the proposed approach can effectively provide appealing composition recommendation to help users take high quality photos with human in the scene.
Fine Granularity Scalability Encryption of MPEG-4 FGS Bitstreams

In this paper, we present an encryption scheme for MPEG-4 FGS which provides the same or a little coarser granularity of scalability after encryption. The scheme encrypts compressed data of each video packet or block independently. Initialization vectors are generated with a method to minimize the overhead. The scalability provided in an encrypted codestream using this scheme enables intermediate nodes to truncate an encrypted bitstream at near R-D optimality directly without decryption, which enhances system security. The scheme has virtually negligible overhead, and produces encrypted codestream with virtually the same error resilience performance as the unencrypted case. These features are very desirable in many applications
UEP Video Transmission Based on Dynamic Resource Allocation in MIMO OFDM System

This paper presents a novel unequal error protection (UEP) video transmission scheme based on dynamic resource allocation in a MIMO-OFDM system in order to improve the video transmission performance over wideband wireless channels. In this new scheme, a low density parity code (LDPC) is combined with a complexity reduced power reallocation algorithm to utilize the excess powers which margin from the powers necessary to meet the modulation level selected under a certain BER constraint. Furthermore, by taking full advantage of the residual excess powers, unequal error protection on important bits of video streams is provided by the LDPC code. Accordingly, the transmission efficiency and quality are both increased. Simulation results have shown that the proposed scheme may achieve great improvement in both systems with or without perfect channel estimation.
QoS-driven scheduling approach using optimal slot allocation for Wireless Body Area Networks

Wireless Body Area Network (WBAN) is a promising type of networks that mainly targets at applications in ubiquitous communication and e-Health services. Different from other types of networks, one important challenge for WBAN is that its quality of service (QoS) requirement, in terms of delivery probability and data rate, will be time varying since human body is a highly dynamic physical environment. Another significant challenge for WBAN is that energy efficiency needs to be guaranteed in such a resource-limited network. In this paper, a QoS-driven scheduling approach is proposed to address these challenges. We model the WBAN channel as a Markov model as suggested by the emerging IEEE 802.15.6 BAN standard and propose a threshold-based scheme to adjust the transmission order of nodes. The number of slots for each node is optimally assigned according to the QoS requirement while minimizing the energy consumption of nodes. The results from extensive simulations show that the proposed approach can provide high QoS and energy efficiency under different network conditions, especially in highly heterogeneous ones in WBAN.
Layered compression for high dynamic range depth

With the rapid development of depth data acquisition technology, the high precision depth becomes much easier to access in real-time by depth sensors, and the generated high dynamic range (HDR) depth is widely adopted to benefit the depth assistant applications. Accordingly, the HDR depth compression becomes essential for the efficient depth storage and transmission. In this paper, we introduce a layered compression framework for HDR depth to achieve efficient and low-complexity depth compression. To leverage the state-of-art 8-bit image/video encoders, the HDR depth is partitioned into two layers: most significant bit (MSB) layer and least significant bit (LSB) layer. For MSB layer, an error controllable pixel domain encoding scheme is proposed to guarantee the compatibility for existing 8-bit codec by controlling quantization errors added back to LSB layer. Meanwhile, the efficient major color extraction and adaptive quantization enhance the coding performance of MSB layer. For LSB layer, the layer data with limited dynamic range is compressed by normal 8-bit image/video based encoding scheme. The experimental results demonstrate that our coding scheme can achieve real-time depth compression with the satisfactory reconstruction quality. The encoding time is less than 31ms/frame and the decoding time is around 20ms/frame in average. Our compression scheme can be easily integrated into the real-time depth transmission system.
Sparse dyadic mode for depth map compression

In order to enable new video applications such as 3DTV and free-viewpoint video, new data formats including both 2D video sequences and corresponding depth map sequences have been proposed. One major characteristic making the depth maps different from video frames is that they typically consist of homogeneous areas separated by sharp edges representing depth discontinuities. Another characteristic of depth map sequences is that the edges exhibit quite similar boundary behaviors as the edges in the corresponding video frames. In this paper, we propose a novel sparse dyadic mode in the design of an efficient depth map compression algorithm through appropriately exploiting these characteristics. With sparse representations of depth blocks and effective reference of edge information from the corresponding video frames, sparse dyadic mode can achieve up to 1.5 dB gain on rendering quality as compared to depth sequences coded using MVC at the same bitrate.
Contemporary ubiquitous media services: Content recommendation and adaptation

Recent rapid advancement in both pervasive mobile computing and cloud service has been driving numerous new applications in the ubiquitous media consumption. To provide mobile user with richer experiences, it is desired for the service providers to offer highly relevant recommendations of media content to the users by exploring user-user, user-media and user-context relationships. Furthermore, contemporary media services also need to address potential presentation mismatch between high quality high resolution media data in the cloud data centers and low resolution terminal capability of the ubiquitous mobile users. This paper attempts to examine several relevant recent developments in ubiquitous media services, especially in the area of content recommendation and user centric content adaptation. Based on current technology trends, we envisage the bright future of ubiquitous media services as pervasive mobile computing and cloud service advance to next level of technology penetration.