nils-herrmann/clean_scirepeval huggingface dataset:
Supporting Ranked Boolean Similarity Queries in MARS

To address the emerging needs of applications that require access to and retrieval of multimedia objects, we are developing the Multimedia Analysis and Retrieval System (MARS). In this paper, we concentrate on the retrieval subsystem of MARS and its support for content-based queries over image databases. Content-based retrieval techniques have been extensively studied for textual documents in the area of automatic information retrieval. This paper describes how these techniques can be adapted for ranked retrieval over image databases. Specifically, we discuss the ranking and retrieval algorithms developed in MARS based on the Boolean retrieval model and describe the results of our experiments that demonstrate the effectiveness of the developed model for image retrieval.
Towards good web conferencing system design for ubi-media collaboration

Media, data and documents are becoming ubiquitous in the past decade, across time zones and across organization boundaries. Web conferencing systems emerged as effective tools for people to communicate and collaborate. These systems combine multiple distributed applications to manipulate multimedia content within a conferencing session, and achieved great results. However, despite great development in such systems, current products on the market are still far from perfect in many aspects. In this paper, we first present an overview of existing systems, and then identify good system design principles based on our own experience with the existing systems. Finally, we outline several interesting research directions that may further enhance userspsila collaboration experience.
Relevance feedback: a power tool for interactive content-based image retrieval

Content-based image retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many systems built. While these research efforts establish the basis of CBIR, the usefulness of the proposed approaches is limited. Specifically, these efforts have relatively ignored two distinct characteristics of CBIR systems: (1) the gap between high-level concepts and low-level features, and (2) the subjectivity of human perception of visual content. This paper proposes a relevance feedback based interactive retrieval approach, which effectively takes into account the above two characteristics in CBIR. During the retrieval process, the user's high-level query and perception subjectivity are captured by dynamically updated weights based on the user's feedback. The experimental results over more than 70000 images show that the proposed approach greatly reduces the user's effort of composing a query, and captures the user's information need more precisely.
A portable solution for automatic lecture room camera management

Rapid advances in technology and decreasing costs have made it possible to attach high resolution video cameras to just about any computer and record the interactions in a lecture room. Additionally, lecture rooms may be outfitted with several cameras for this purpose. However, recording the interactions alone does not create effective video. In this paper we present a method for not only recording, but also editing in real-time, lectures. Unlike previous work, the system is highly portable, allowing quick set-up in various types of lecture rooms. This portability is achieved by using the abstraction of virtual cameramen and physical cameras, and a scriptable interface to the editing rules
Multimodal Deep Embedding via Hierarchical Grounded Compositional Semantics

For a number of important problems, isolated semantic representations of individual syntactic words or visual objects do not suffice, but instead a compositional semantic representation is required; for example, a literal phrase or a set of spatially concurrent objects. In this paper, we aim to harness the existing image–sentence databases to exploit the compositional nature of image–sentence data for multimodal deep embedding. In particular, we propose an approach called hierarchical-alike (bottom–up two layers) multimodal grounded compositional semantics (hiMoCS) learning. The proposed hiMoCS systemically captures the compositional semantic connotation of multimodal data in the setting of hierarchical-alike deep learning by modeling the inherent correlations between two modalities of collaboratively grounded semantics, such as the textual entity (with its describing attribute) and visual object, the phrase (e.g., subject-verb–object triplet), and spatially concurrent objects. We argue that hiMoCS is more appropriate to reflect the multimodal compositional semantics of the image and its narrative textual sentence, which are strongly coupled. We evaluate hiMoCS on the several benchmark data sets and show that the utilization of the hiMoCS (textual entities and visual objects, textual phrase, and spatially concurrent objects) achieves a much better performance than only using the flat grounded compositional semantics.
You Are What You Eat: Exploring Rich Recipe Information for Cross-Region Food Analysis

Cuisine is a style of cooking and usually associated with a specific geographic region. Recipes from different cuisines shared on the web are an indicator of culinary cultures in different countries. Therefore, analysis of these recipes can lead to deep understanding of food from the cultural perspective. In this paper, we perform the first cross-region recipe analysis by jointly using the recipe ingredients, food images, and attributes such as the cuisine and course (e.g., main dish and dessert). For that solution, we propose a culinary culture analysis framework to discover the topics of ingredient bases and visualize them to enable various applications. We first propose a probabilistic topic model to discover cuisine-course specific topics. The manifold ranking method is then utilized to incorporate deep visual features to retrieve food images for topic visualization. At last, we applied the topic modeling and visualization method for three applications: 1) multimodal cuisine summarization with both recipe ingredients and images, 2) cuisine-course pattern analysis including topic-specific cuisine distribution and cuisine-specific course distribution of topics, and 3) cuisine recommendation for both cuisine-oriented and ingredient-oriented queries. Through these three applications, we can analyze the culinary cultures at both macro and micro levels. We conduct the experiment on a recipe database Yummly-66K with 66,615 recipes from 10 cuisines in Yummly. Qualitative and quantitative evaluation results have validated the effectiveness of topic modeling and visualization, and demonstrated the advantage of the framework in utilizing rich recipe information to analyze and interpret the culinary cultures from different regions.
New direct approaches to robust sound source localization

When more than two microphones are used, the traditional time-delay-of-arrival (TDOA) based sound source localization (SSL) approach involves two steps. The first step computes TDOA for each microphone pair, and the second step combines these estimates. This two-step process discards relevant information in the first step, thus degrading the SSL accuracy and robustness. Although less used, one-step processes do exist. In this paper, we review these processes, create a unified framework, and introduce two new one-step algorithms. We compare our proposed approaches against existing 1and 2-step approaches and demonstrate significantly better SSL performance.
Sound source localization for circular arrays of directional microphones

Previous research in sound source localization has helped increase the robustness of estimates to noise and reverberation. Circular arrays are of particular interest for a number of scenarios, particularly because they can be placed in the center of the sources. First, that improves the sound capture due to the reduced distance. Second, it helps on the direction estimation, not only because of the reduced distance, but also because it increases the angle differences. Nevertheless, most research on circular arrays focused on the case of omni-directional microphones. In this paper, we present a new algorithm for sound source localization developed specifically for directional microphones. Results obtained from real meeting room setups show a typical error of less than 3 degrees.
View-Based Discriminative Probabilistic Modeling for 3D Object Retrieval and Recognition

In view-based 3D object retrieval and recognition, each object is described by multiple views. A central problem is how to estimate the distance between two objects. Most conventional methods integrate the distances of view pairs across two objects as an estimation of their distance. In this paper, we propose a discriminative probabilistic object modeling approach. It builds probabilistic models for each object based on the distribution of its views, and the distance between two objects is defined as the upper bound of the Kullback-Leibler divergence of the corresponding probabilistic models. 3D object retrieval and recognition is accomplished based on the distance measures. We first learn models for each object by the adaptation from a set of global models with a maximum likelihood principle. A further adaption step is then performed to enhance the discriminative ability of the models. We conduct experiments on the ETH 3D object dataset, the National Taiwan University 3D model dataset, and the Princeton Shape Benchmark. We compare our approach with different methods, and experimental results demonstrate the superiority of our approach.
Breaking the clock face HIP [Web services human interactive proofs]

Web services designed for human users are being abused by computer programs (bots). The bots steal thousands of free email accounts in a minute, participate in online polls to skew results, and irritate people in chat rooms. These real-world issues have recently generated a new research area called human interactive proofs (HIP), whose goal is to defend Web services from malicious attacks by differentiating bots from human users. For a HIP challenge to be effective, it needs to be both easy for human and robust against bots attacks. Recently, there is a new HIP design which is based on telling time from a clock face. This is a very innovative idea and quite easy for human to pass. However, its robustness to attacks needs verification. We present an algorithm that can break the clock face HIP at 87.4%.
Exploiting Click Constraints and Multi-view Features for Image Re-ranking

Image re-ranking is effective in improving performance of text-based image searches. However, improvements from existing re-ranking algorithms are limited by two factors: one is that the associated textual information of images often mismatches their actual visual contents; the other is that a visual's features cannot accurately describe the semantic similarities between images. In this paper, we adopt click data to bridge the semantic gap. We propose a novel multi-view hypergraph-based learning (MHL) method that adaptively integrates click data with varied visual features. In particular, MHL considers pairwise discriminative constraints from click data to maximally distinguish images with high click counts from images with no click counts, and a semantic manifold is constructed. It then adopts hypergraph learning to build multiple manifolds from varied visual features. Finally, MHL integrates the semantic manifold with visual manifolds through an iterative optimization procedure. The weights of different manifolds and the re-ranking score are simultaneously obtained after using this optimization strategy. We conduct experiments on real world datasets and the results demonstrate that MHL outperforms state-of-the-art image re-ranking methods.
Segmenting visual actions based on spatio-temporal motion patterns

The analysis of human action captured in video sequences has been a topic of considerable interest in computer vision. Much of the previous work has focused on the problem of action or activity recognition, but ignored the problem of detecting action boundaries in a video sequence containing unfamiliar and arbitrary visual actions. This paper presents an approach to this problem based on detecting temporal discontinuities of the spatial pattern of image motion that captures the action. We represent frame to frame optical-flow in terms of the coefficients of the most significant principal components computed from all the flow-fields within a given video sequence. We then detect the discontinuities in the temporal trajectories of these coefficients based on three different measures. We compare our segment boundaries against those detected by human observers on the same sequences in a recent independent psychological study of human perception of visual events. We show experimental results on the two sequences that were used in this study. Our experimental results are promising both from visual evaluation and when compared against the results of the psychological study.
Secure image communication using blind source separation

In this paper, an image encryption method is proposed by using the linear mixing model of blind source separation (BSS). It can simultaneously encrypt multiple images with the same size by mixing them with the same number of statistically independent key images, the size of which is equal to that of the images to be encrypted. Since these multiple images cover mutually through mixing among them while the key images cover them, and there is not any restriction on the key space, the proposed method has high level of security. Computer simulation results show its validity.
A video editing system based on the depth information

In this paper, we propose a method to measure the distance between the camera and object of the scene. In our method, first we calculate the distance between the camera and the scene, and then measure the depth of the objects of the scene. The measurement of depth needs some information from camera, so we use the two symmetric frames to calculate the parameters of camera. In the second step, to remove radial and lens distortion, third, to rectify the input images, finally, use the block-matching stereo algorithm and graph cut-based algorithm with SAD to find the disparity. When we finish the measurement of depth of the background in the video, we can use the information to implant the objects and adjust their size automatically.
A queue-based analysis for Denial of Service attacks on Voice over IP proxies

A simple and yet effective denial of service (DoS) attack on voice over IP (VoIP) proxies that based on session initiation protocol (SIP), is to flood the server with requests that their addresses do not exist and are irresolvable. Different security schemes and possible attacks have studied from the qualitative view on the most of network security researches and these researches are less considered the quantitative analysis. In this paper, a queueing model has suggested for evaluation of these attacks and the server under attack is modeled by a two-dimensional Markov chain. We can develop a memory effective algorithm for the calculating of stationary probability distribution by the help of this model, which we can use it for finding other interesting performance metrics like the buffer occupancy percentages for regular requests and attack requests. This paper proposes a more general analytical approach for the study of security measures of a computer network under this kind of attacks and we hope that this method shows a new way for the quantitative evaluation of more complicated security cases in computer networks.
Emergency SMS

Delivering first aid before transferring patients to hospital is among keys to survival. Moreover, calling the emergency center as soon as possible and providing brief information about the patient are helpful for the emergency center to dispatch specialized medical team and equipments proportionate to the conditions of the patient. Mobile phone is a device which many people use and always carry with them. One more thing is that SMS (short message service) stands as a favorite service in mobile network, used to exchange short messages and featuring low cost, non-stop lines of dispatch, possibilities for offline work and so forth. This paper puts forward procedures of calling an emergency center through SMS in which whenever a patient feels sick, it is enough just to press a button on mobile phone for seconds to activate a special program which automatically sends a message for the emergency center, the family doctor and a next of kin, carrying residence address (by using GPS system), personal information (age, name, etc.) and a brief medical record (current illnesses, individual second habits like smoking, etc.). As a follow-up, the emergency team can examine the records and subsequently send a medic and a specialized doctor for possible diseases (for example a cardiac medic for potential heart attack). Family doctor and relatives on the other hand can be briefed on the patient's conditions. The project is written by the Java 2 Micro Edition (J2ME) programming language and tested on a Nokia N71 mobile phone
Rescue SMS

Earthquake is one of the natural disasters which have a lot of victims each year. If the rescue mission for saving victims be done in first hours after the earthquake, the number of earthquake victims can be lowered. Different methods had been proposed to find victims under devastated buildings which some of them are expensive and time consuming and aren't applicable in under developing countries. So, here we propose a method for rescuing earthquake victims using mobile phone and SMS (short message service) service. In this method, the Earthquake Emergency Center send an SMS message to all people in place which earthquake was happen that asking about people condition. A special program which is running on recipient mobile phone, get this message and then ask from user about his health condition and does he need rescue team help. If the user didn't reply or request help, a help request SMS containing help request message and current location of mobile phone will be sent to Earthquake Emergency Center automatically. In addition, the victim mobile phone starts to play special pattern of beeps so rescue team persons and rescue robots can find the place of victim under devastated buildings. This method has low cost and can be run on most available phones. This program written by the J2ME (Java 2 Micro Edition) and tested on different mobile phones like Nokia 6680 and Nokia N71
Steganography in TeX documents

Steganography is a method for hidden exchange of information by hiding data in a cover media such as image or sound. Text Steganography is one of the most difficult methods because a text file is not a proper media to hide data in it. In this paper we propose a new text Steganography method. In this method, we hide data in TeX documents. This method hides the data in places where there is a ligature such as ¿fi¿.
Parental control based on speaker class verification

Restricting children access to materials unsuitable for them such as violence scenes is very important for parents. So there is a feature named Parental Control in devices such as televisions and computers to define the contents children can access. The parental control setting must be protected from children and is usually done by a password. In this paper, we propose a new method for distinguishing between adult users and child users based on human speech. In our proposed method, the user must say a word and the adult users are identified by processing the speech. Our current implementation has 92.5% accuracy for distinguishing adult users from children.
An Improved Version of Persian/Arabic Text Steganography Using "La" Word

By expanding communication, in some cases there is a need for hidden communication. Steganography is one of the methods used for hidden exchange of information. Steganography is a method to hide the information under a cover media such as image or text. One of the text steganography methods for Persian and Arabic texts is "La" steganography method. But that method increases the file size and changes the apparent of the text. In this paper a method for solving these problems is proposed. In Persian and Arabic, each letter can have four different shapes regarding to its position in the word. In this method by using this feature of Persian and Arabic languages and the way which documents are saved in the Unicode Standard, the above problems are solved.
Knapsack Model for Pixel Based Skin Detection

Skin detection has different applications in computer vision such as face detection, human tracking and adult content filtering. One of the major approaches in skin detection is pixel based skin detection which mark pixels as skin pixels based on their color. In this paper, we formally define the pixel based skin detection problem and model skin detection as a Knapsack problem. Then we formulate the maximum accuracy which can be reached by training on a given data set. Finally, we study one of the common pixel based skin detection methods in our Knapsack model.
A Skew Resistant Method for Persian Text Segmentation

Using OCR programs is one of the best ways to convert written and printed documents into digital form. The first phase in OCR is segmenting the input image and identifying text and non-text regions. This paper proposes a new method for segmentation of Persian printed texts which is based on the ink spread effect. Considering that the Persian scripts are very different from the English script, most methods proposed for the English script have not rendered good results for the Persian scripts. The method proposed in this paper has been designed considering the special features of the Persian scripts. In addition, one of the most important characteristics of this method is resistance to skew. Moreover, the proposed approach is directly applicable to Arabic scripts
Persian/Arabic Unicode Text Steganography

Sending information secretly and communicating covertly have been of great interest for ages. On the other hand, text documents have been widely used and consequently various methods for hiding information in texts (text steganography) have been developed so far. In this paper a new method is proposed to hide information in digital Persian and Arabic Unicode texts.In Persian and Arabic, each letter can have four different shapes regarding to its position in the word. In this method by using this feature of Persian and Arabic languages and the way which documents are saved in the Unicode Standard, the information is hidden in Unicode text documents. This method has a good hiding capacity because it hides one bit in each word. Also this method does not make any apparent changes in the original text and have a perfect perceptual transparency.