nils-herrmann/clean_scirepeval huggingface dataset:
Learning Consistent Feature Representation for Cross-Modal Multimedia Retrieval

The cross-modal feature matching has gained much attention in recent years, which has many practical applications, such as the text-to-image retrieval. The most difficult problem of cross-modal matching is how to eliminate the heterogeneity between modalities. The existing methods (e.g., CCA and PLS) try to learn a common latent subspace, where the heterogeneity between two modalities is minimized so that cross-matching is possible. However, most of these methods require fully paired samples and suffer difficulties when dealing with unpaired data. Besides, utilizing the class label information has been found as a good way to reduce the semantic gap between the low-level image features and high-level document descriptions. Considering this, we propose a novel and effective supervised algorithm, which can also deal with the unpaired data. In the proposed formulation, the basis matrices of different modalities are jointly learned based on the training samples. Moreover, a local group-based priori is proposed in the formulation to make a better use of popular block based features (e.g., HOG and GIST). Extensive experiments are conducted on four public databases: Pascal VOC2007, LabelMe, Wikipedia, and NUS-WIDE. We also evaluated the proposed algorithm with unpaired data. By comparing with existing state-of-the-art algorithms, the results show that the proposed algorithm is more robust and achieves the best performance, which outperforms the second best algorithm by about 5% on both the Pascal VOC2007 and NUS-WIDE databases.
The structural analysis based on modern design method

Our traditional design is mainly based on producing experiences according to mechanical and mathematical formulas, diagrams, manuals and so on. Therefore, the finished product is functional but long design period and high cost are required. Nowadays, various modern design methods are more and more applied. The methods help to avoid aimless and random of the empirical design, to increase design scientificity, to bring down development cost, to shorten developing period and to improve product's quality. This paper presents based on the modern design methods of finite element method and virtual prototype technology how to build parameterized three-dimensional material model of mechanical system by means of three-dimensional modeling software, UG, how to apply ADAMS, a dynamics virtual prototype software of mechanical system, to build rigid body model, how to establish Model Neutral File of flexible body components by means of finite element method software, ANSYS, and how to build flexible body model by means of ADAMS. It also presents when force and constraint are applied to each component, modal analysis of multi-body system dynamics three-dimensional visible intensity and vibration is undertaken and modal mode and frequency are inspected. This paper researches the initial attempt of applying advanced design, analysis and simulation techniques in design of ships crane. It also offers some feasible experiences and methods for the virtual design, dynamic design and structure virtual analysis of ships crane.
Web-Scale Near-Duplicate Search: Techniques and Applications

This paper presents some of the most recent advances in the research on Web-scale near-duplicate search and explores the potential for bringing this research a substantial step further. It contains high-quality contributions addressing various aspects of the Web-scale near-duplicate search problem in a number of relevant domains. The topics range from feature representation, matching, and indexing from different novel aspects to the adaptation of current technologies for mobile media search and photo archaeology mining.
Descriptive local feature groups for image classification

In the conventional bag of visual words (BoW) based image representation, single visual word is not discriminative enough and the spatial contextual information among local image features is ignored. In this paper, descriptive local feature groups are proposed to address these two problems. First, local image features are refined by slightly transforming the original image. Then they are clustered and represented by visual words. Second, the candidate local feature groups are generated by searching the neighbors of every local image features. This kind of grouping shows more discriminative power than a single feature and the local spatial contexts can be catched. Third, we obtain the groups more descriptive to the object category by defining a significance score and the groups with high score are selected. Finally, the high order descriptive local feature groups are integrated to the vector based object categorization framework by a feature reweighting strategy. Experimental results on Scene-15 and Caltech 101 demonstrate the superior performance of our method.
Social Multimedia Ming: From Special to General

Social multimedia is the hybrid of social media and multimedia. Social multimedia mining employs data mining techniques to understand the association among content, user and interaction in social multimedia. It has three basic problems at basis, micro and macro association levels. This paper extends the current interpretation of social multimedia mining as processing multi-modal individual objects, to a generalized definition beyond modality and beyond object. Cross-OSN (Online Social Networking) data mining, an instantiation to general social multimedia mining, is then positioned with main challenges, review of current studies and future directions.
A multi-layer key stream based approach for joint encryption and compression of H.264 video

Encryption of multimedia video data has been extensively studied. However, a pipelined method of compression followed by encryption is not always feasible and springs new challenges, namely the effect of visual degradation and the computational cost of the encryption process. Recently, joint encryption and compression techniques, which aim to encrypt the video as it is being compressed by the encoder, have gained popularity. This work aims to develop a lightweight yet effective multi-layer key stream based technique to encrypt video data by performing joint encryption and compression. Our joint encryptor-encoder performs almost as fast as a normal H.264 compression-only encoder. The multi-layer key stream we use for encryption is extracted from the underlying video structure itself, thus thwarting (piracy) key generators. It also facilitates efficient handing of packet loss in real-time transmission. Results show our method produces almost complete obscuration of the video, a consistent degradation for diverse scenes, and format compliant encrypted H.264 video.
Optimum Detection of Image-Adaptive Watermarking in the DCT Domain

Digital watermarking is an efficient and promising means to protect intellectual properties. Spread spectrum (SS) is one of the most widely used watermarking schemes, and can be further facilitated by adapting the watermark strength to the host signal. In this paper we address the problem of optimum blind detection of SS watermarks in the DCT domain, where Watson's non-linear perceptual model is used for the modulation of the watermarks. The basic idea is to transform the DCT coefficients to a perceptually uniform domain and perform Bayesian hypothesis testing in that domain. Simulation results show the superior performance of the proposed scheme over the conventional linear correlation detector (LCD).
A protocol for simultaneous real time playback and full quality storage of streaming media

In this paper, we introduce the new problem of simultaneous streaming of a single media bitstream to multiple devices with different quality of service (QoS) requirements. In particular, we address simultaneous streaming of a single video stream for both real time playback and full quality storage, where the QoS requirements of the two targets are different. We design a joint streaming protocol to fully exploit the available bandwidth to deliver both real-time and retransmitted packets simultaneously, as bandwidth allows. Preliminary results show that the proposed joint streaming protocol can simultaneously address the requirements of both real-time playback and less time-critical, higher quality storage of streaming media.
Structure-Preserving Hybrid Digital-Analog Video Delivery in Wireless Networks

Hybrid digital-analog (HDA) transmission has gained increasing attention recently in the context of wireless video delivery , for its ability to simultaneously achieve high transmission efficiency and smooth quality adaptation. However, previous systems are optimized solely based on the mean squared error criterion without taking the perceptual video quality into consideration. In this work, we propose a structure-preserving HDA video delivery system, named SharpCast, to improve both the objective and subjective visual quality. SharpCast decomposes a video into a content part and structure part. The latter is important to the human perception and therefore is protected with a robust digital transmission scheme. Then, the energy-intensive part in the content information is extracted and transmitted in digital for energy efficiency while the residual is transmitted in analog to achieve the desired smooth adaptation. We formulate the resource (power and bandwidth) allocation problem in SharpCast and solve the problem with a greedy strategy. Evaluations over nine standard 720p video sequences show that the proposed SharpCast system outperforms the state-of-the-art digital, analog, and HDA schemes by a notable margin in both peak signal-to-noise ratio (PSNR) and structural similarity (SSIM).
Perceptual Image Hashing Method Using Contourlet HMT Model

Image hashing finds extensive applications in content authentication, database search. This paper develops a novel algorithm for generating an image hash based on contour let hidden Markov tree (HMT) model and SVD. The contour let transform is a new two-dimensional extension of the wavelet transform using multi scale and directional filter banks. It effectively captures smooth contours that are the dominant feature in natural images. The contour let HMT model can capture all inter-scale, inter-direction, and inter-location dependencies of contour let coefficients using a few statistics parameters. These parameters are stable to content-preserving modifications and at the same time, are sensitive to malicious tampering. We introduce SVD and randomization to produce the hash string. Experimental results show that the proposed hashing methods can provide excellent security and robustness.
SDNAN: Software-defined networking in ad hoc networks of smartphones

In this paper, SDNAN, a first attempt to implement software-defined networking (SDN) over a wireless ad hoc network of smartphones, is presented. Its modular ad hoc network management structure can be easily modified and extended. Its abstractions and interfaces allow components to communicate without knowing how other components work. Third-party applications can use the interfaces to access the ad hoc network, significantly reducing development time and program complexity. A prototype system has been implemented on Android smartphones over Wi-Fi and achieved good preliminary results.
Removing camera fingerprint to disguise photograph source

Sensor-based camera source identification (CSI) is believed to be an effective tool for linking a photograph to its source camera. In this paper, we propose a photo response non-uniformity (PRNU) removing attack on CSI. The PRNU fingerprint is a kind of multiplicative noise, and is believed to be difficult to be removed from an image. In this work, both the pattern and magnitude of the PRNU fingerprint of an unaltered image are estimated first, then it is subtracted from the target image. Theoretical analysis and experimental results show that the PRNU fingerprint can be removed using only common processing techniques without introducing visual artefact, therefore CSI can be easily defeated.
Rate-Distortion Optimized Transmission Power Adaptation for Video Streaming over Wireless Channels

An important characteristic of video transmission over wireless channels is that the channel is error-prone and the compressed video data is highly sensitive to errors. The transmission errors will cause decoding failure which will distort the reconstructed pictures. One of the challenging issues in wireless video communication system design is to minimize the overall energy consumption and maximize the operational lifetime of the devices. In this work, we focus on the energy consumption in wireless video transmission. Based on a transmission distortion model, we develop a rate-distortion optimized transmission power adaptation scheme for video streaming over wireless channels. Our experimental results demonstrate that this scheme is able to significantly improve the video quality under the transmission power constraints.
Cross-Layer Design of Source Rate Control and Qos-Aware Congestion Control for Wireless Video Streaming

Cross-layer design has been used in streaming video over the wireless channels to optimize the overall system performance. In this paper we extend our previous work (i.e. joint design of source rate control and congestion control for video streaming over the Internet) in P.Zhu et al., (2005) and propose a cross-layer design approach for wireless video streaming. By jointly designing the source rate control at the application layer and congestion control at the transport layer, and taking advantage of MAC layer information, our approach can avoid the throughput degradation caused by transmission error of the wireless channel, and better support the QoS requirements of the application. Simulation results show that the proposed mechanism can significantly improve the playback quality of the application, while maintaining good performance of the transport protocol
Compound image compression using lossless and lossy LZMA in HEVC

We present a compound image compression scheme based on the dictionary-based Lempel-Ziv-Markov chain algorithm (LZMA), under the framework of High Efficiency Video Coding (HEVC). Through matching strings from the sliding window dictionary, LZMA exploits the characteristics of the repeated patterns over the text and graphics regions of compound images, and represents them compactly. To obtain high compression efficiency even for noisy text and graphics contents, we have modified LZMA to support both lossless and lossy compression. We develop and treat it as a new intramode of HEVC. Experimental results show that the proposed scheme achieves significant coding gains for compound image compression. Thanks to the introduction of the lossy LZMA, the compression performance for noisy compound images is improved for more than 5dB in terms of PSNR in comparison with the lossless LZMA scheme.
Joint Design of Source Rate Control and QoS-Aware Congestion Control for Video Streaming over the Internet

This paper proposes an algorithm for joint design of source rate control and congestion control for video streaming over the Internet. At the application layer, with the incorporation of a virtual network buffer management mechanism (VB), the QoS requirements of the application can be translated into the constraints of the source rate and the send rate. At the transport layer, a QoS-aware congestion control mechanism is proposed that strives to meet the send rate constraint derived from VB, by allowing temporary violation of TCP-friendliness when necessary. Long-term TCP-friendliness, nevertheless, is preserved by introducing a rate compensation algorithm. Simulation results show that compared with traditional source rate/congestion control algorithms, this cross-layer design approach can significantly improve the playback quality by reducing the overflow and underflow of the decoder buffer, and improving quality smoothness, while maintaining long-term TCP-friendliness
Influence of social media on performance of movies

The performance of movies in terms of revenue depends on many factors such as its production studio, genre, script quality, pre-release promotion etc, - all of which are traditionally used to estimate their potential success at the box office. Recently however, the “Wisdom of Crowd” and social media have been acknowledged as a strong signal in understanding consumer behavior towards media. In this paper, we discuss the impact of socially generated meta-data mined from the social multimedia sites and study the influence of social media on box- office performance and profitability of movies. Our result shows that various social media signals have varying yet significant impact in predicting the performance of movies. Our research also reveals that popularity of actor captured by follower count on Twitter is most relevant to the success of movie at theaters, and Facebook `like' signal has noise which impedes its analytical credibility.
A format-compliant configurable encryption framework for access control of multimedia

We present a framework for access control of standard-compliant video bitstreams for entertainment purposes. The approach leverages well-known encryption algorithms and maintains standard-compliance of the encrypted bitstream. The standard compliance feature guarantees the inheritance of the error resiliency properties of the video compression standards, and works with many existing network bandwidth adaptation and error control techniques that have been developed for standards-compliant compressed video, thus making it especially suitable for wireless multimedia applications. Standards compliance also allows subsequent signal processing techniques to be applied to the encrypted bitstream. The approach can be applied to any of the common video coding standards. It is also capable of providing layered compromises between security, complexity, delay, bit overhead, etc.
Fully Reversible Privacy Region Protection for Cloud Video Surveillance

Privacy becomes one of the major concerns of cloud-based multimedia applications such as cloud video surveillance. Privacy protection of surveillance videos aims to protect privacy information without hampering normal processing tasks of the cloud. Privacy Region Protection only protects the privacy region while keeping the non-privacy region visually intact to facilitate processing in the cloud. However, full reversibility, i.e. the complete recovery of the original video which is critical to digital investigation and law enforcement has not been properly addressed in privacy region protection. In this paper, we introduce fully reversible privacy region protection into cloud video surveillance and propose a novel fully reversible privacy protection method for H.264/AVC compressed video. All the operations are performed in the compressed domain and avoid lossy re-encoding, so the original H.264/AVC compressed video can be fully recovered. To our best knowledge, the proposed scheme is the first fully reversible one for privacy region protection. Experimental results and performance comparison demonstrate the effectiveness and efficiency of the proposed approach.
Digital watermarking in a perceptually normalized domain

One of the fundamental issues in digital watermarking is to find the best trade-off between imperceptibility and robustness to signal processing. Properties of human visual systems (HVS) have been exploited to achieve this goal. Previously, researchers have made use of frequency sensitivity, luminance sensitivity and visual masking effect of the HVS to adaptively control the amount of watermark energy to be embedded into different transform coefficients of the image. We present an alternative approach that first nonlinearly transforms the original signal to a perceptually uniform domain, then embeds a constant amount of watermark to each sample in this domain. We show that the derivation of an optimal watermark detector is straightforward in this approach, as opposed to some previous approaches. The advantage of exploiting the neighborhood-masking effect is also briefly discussed.
Image-adaptive watermarking using visual models

The huge success of the Internet allows for the transmission, wide distribution, and access of electronic data in an effortless manner. Content providers are faced with the challenge of how to protect their electronic data. This problem has generated a flurry of research activity in the area of digital watermarking of electronic content for copyright protection. The challenge here is to introduce a digital watermark that does not alter the perceived quality of the electronic content, while being extremely robust to attack. For instance, in the case of image data, editing the picture or illegal tampering should not destroy or transform the watermark into another valid signature. Equally important, the watermark should not alter the perceived visual quality of the image. From a signal processing perspective, the two basic requirements for an effective watermarking scheme, robustness and transparency, conflict with each other. We propose two watermarking techniques for digital images that are based on utilizing visual models which have been developed in the context of image compression. Specifically, we propose watermarking schemes where visual models are used to determine image dependent upper bounds on watermark insertion. This allows us to provide the maximum strength transparent watermark which, in turn, is extremely robust to common image processing and editing such as JPEG compression, rescaling, and cropping. We propose perceptually based watermarking schemes in two frameworks: the block-based discrete cosine transform and multiresolution wavelet framework and discuss the merits of each one. Our schemes are shown to provide very good results both in terms of image transparency and robustness.
Reactive power-voltage integrated control method based on MCR

In power system, the voltage pulsation and deficiency or surplus of reactive power will have a great effect on the quality of electric power supply. Through the appropriate and effective way of compensation, we can keep the balance of reactive power in the maximum degree by the maintenance of acceptable voltage. That's to say, quality of power supply can be improved greatly by the synthetic compensation of reactive power and voltage. This paper firstly describes the principles of synthetic compensation of reactive power and voltage, then introduces the analyzes the principle of magnetically controlled reactor-MCR in detail and derives the characteristics, lastly designs a controlling strategy of reactive power and voltage based on MCR, so as to achieve the goal of dynamic reactive power compensation.
Spatial-temporal error concealment with side information for standard video codecs

Error concealment (EC) is important for transmitting video over error prone networks such as the Internet or wireless networks. Different EC strategies have their own advantages for different scenarios. However, it is generally difficult for the decoder to figure out which strategy works the best for a specific case. This paper proposes to use data embedding to convey the necessary high level side information in a standard compliant way to help improve the decoder's EC performance. We show that the EC "mode" information (i.e.., whether spatial EC or temporal EC should be used) is critical for a spatial-temporal EC approach.