nils-herrmann/clean_scirepeval huggingface dataset:
A Study of DWT and SVD Based Watermarking Algorithms for Patient Privacy in Medical Images

Information and Communication Technologies (ICT) are being adopted widely to improve citizen's health care. Health information systems (HIS) of different hospitals exchange electronic medical records including digital medical images of patients. Medical images and accompanying reports have special requirement of protecting the privacy of the patient by not revealing personal particulars especially when they are transmitted over networks. To increase the security of medical images and preserve patients' privacy, digital watermarking has been proposed. In this paper, we study the performance of three different watermarking algorithms (DWT, SVD and DWT-SVD based watermarking algorithms). We have created two different watermarks with same watermark information but with different characteristics - one is QR Code as watermark image which is capable of carrying large information in small space, while the other one is a normal text image watermark and embedded inside medical images. We, then, have assessed the quality of watermarked images obtained after embedding the watermarks using both objective (PSNR) as well as subjective (opinions from physicians, a radiologist and a medical physicist) methods and found that watermarking has not resulted in loss of medical information. Further, we have conducted several experiments to evaluate the performance of these algorithms in terms of robustness, capacity, and embedding time. Experimental results show that DWT based method is suitable for medical applications where embedding time and imperceptibility are prime concerns while SVD based methods are suitable for medical applications where robustness and capacity are the main concerns.
A survey of quality of service in IEEE 802.11 networks

Developed as a simple and cost-effective wireless technology for best effort services, IEEE 802.11 has gained popularity at an unprecedented rate. However, due to the lack of built-in quality of service support, IEEE 802.11 experiences serious challenges in meeting the demands of multimedia services and applications. This article surveys 802.11 QoS schemes, including service differentiation in the MAC layer, admission control and bandwidth reservation in MAC and higher layers, and link adaptation in the physical layer, designed to meet these challenges by providing the necessary enhancements for the required QoS. Furthermore, the article addresses issues that arise when end-to-end QoS has to be guaranteed in today's pervasive heterogeneous wired-cum-wireless networks. Among these challenges, protocol interoperability, multihop scheduling, full mobility support, and seamless vertical handoff among multiple mobile/wireless interfaces are specifically addressed.
Loss tolerance scheme for 3D progressive meshes streaming over networks

Nowadays, the Internet provides a convenient medium for sharing complex 3D models online. However, transmitting 3D progressive meshes over networks may encounter the problem of packets loss that can lead to connectivity inconsistency and distortion of the reconstructed meshes. In this paper, we combine reliable and unreliable channels to reduce both time delay and mesh distortion, and we propose an error-concealment scheme for tolerating packet loss when the meshes are transmitted over unreliable network channels. When the loss of connectivity data occurs, the decoder can predict the geometry data and mesh connectivity information, and construct an approximation of the original mesh. Therefore, the proposed error-concealment scheme can significantly reduce the data size required to be transmitted over reliable channels. The results show that both the computational cost of our error-concealment scheme and the distortion introduced by our scheme are small.
Synchronization Representation and Traffic Source Modeling in Orchestrated Presentation

Multimedia applications comprise several media streams, which are semantically synchronized at different time instants. The application behavior is stored along with the multimedia database using representation mechanisms such as OCPN (object composition Petri nets) or dynamic timed Petri nets (DTPN). It is imperative that one translates the application behavior to the corresponding schedulable entities, such as packets, so that the performance engineering of any system can be done, using the traffic model arising out of the (media related) application behavior as opposed to individual media level behavior. This requires that a function be defined, which takes the stored temporal representation as input and produces packets as output, preserving the semantic relationships among the streams. The authors propose a methodology based on probabilistic, attributed context free grammar (PACFG) to address this issue. They demonstrate the appropriateness of this methodology by applying it to the OCPN/DTPN representation of a typical multimedia application vis-a-vis orchestrated presentation.
Distributed video presentations

Considers a distributed video server environment where video movies need not be stored entirely in one server. Blocks of a video movie are be distributed and replicated over multiple video servers. Customers are served by one video server. This video server, termed the originating server, might have to interact with other servers for downloading missing blocks of the requested movie. We present three types of presentation plans that an originating server can possibly construct for satisfying a customer's request. A presentation plan can be considered as a detailed (temporally synchronized) sequence of steps carried out by the originating server for presenting the requested movie to the customer. The creation of presentation plans involves obtaining commitments from other video servers and the network service provider, as well as making local resource commitments, within the limitations of available bandwidth, available buffer and customer consumption rates. For evaluating the goodness of a presentation plan, we introduce two measures of optimality for presentation plans: minimizing the waiting time for a customer and minimizing the access bandwidth. We present algorithms for computing optimal presentation plans and compare their performance experimentally. We have also mathematically proved certain results for the presentation plans.
Region graph based method for multi-object detection and tracking using depth cameras

In this paper, we propose a multi-object detection and tracking method using depth cameras. Depth maps are very noisy and obscure in object detection. We first propose a region-based method to suppress high magnitude noise which cannot be filtered using spatial filters. Second, the proposed method detect Region of Interests by temporal learning which are then tracked using weighted graph-based approach. We demonstrate the performance of the proposed method on standard depth camera datasets with and without object occlusions. Experimental results show that the proposed, method is able to suppress high magnitude noise in depth maps and detect/track the objects (with and without occlusion).
Protocol for collaborative multimedia presentations

Many multimedia presentation applications involve the retrieval of objects from more than one collaborating server. For instance, we can consider distributed video servers where blocks of movies are distributed over a set of servers. Blocks of a movie from different video servers have to be retrieved and presented continuously without any gaps in the presentation. Such applications first need an estimate of the available network resources to each of the collaborating servers in order to identify a schedule for retrieving the objects composing the presentation. A collaborating server can suggest modifications to the retrieval schedule depending on its load. These modifications can potentially affect the retrieval schedule for other collaborating applications. In this paper, we propose an application sub-layer protocol, the Resource Lock Commit Protocol (RLCP), for handling the negotiation and commitment of the resources required for a collaborative multimedia presentation application.
On Supporting High-Quality 3D Geometry Multicasting over IEEE 802.11 Wireless Networks

With significant improvements in both wireless technologies and computational capabilities of mobile devices, it is now possible to exchange and render 3D graphics over wireless networks on mobile devices such as PDAs and laptops. In this paper, we consider a typical scenario where users holding mobile devices of different display resolutions and rendering capabilities request the same 3D object in an IEEE 802.11 wireless LAN. Several schemes are proposed. First, to support high-quality 3D content multicasting, we analyze the characteristics of 3D data and choose the minimum data set for unicast in order to avoid excessive bandwidth consumption. Then, a transcoding algorithm is proposed to address the issue of multiuser diversity. In addition, to take advantage of the nature of broadcast in wireless medium and further mitigate the issue of serious resource usage due to large data size, we propose to broadcast certain less important refinement data. With the proposed hybrid unicast/broadcast transmission scheme and a packet overhearing mechanism, good scalability can be achieved. Finally, we schedule the unicast according to users' experienced link condition to handle user mobility. Simulation results show that the proposed schemes in combination can efficiently achieve the dual objectives of low transmission delay and small distortion.
PicoLife: A Computer Vision-based Gesture Recognition and 3D Gaming System for Android Mobile Devices

Pico Life is envisioned to be an augmented reality game in which 3D characters will be controlled by hand gestures on Android smart phones. Pico Life is currently powered by two mobile optimized engines: (1) The computer vision engine that runs our advanced object tracking program for hand tracking and (2) The 3D engine that runs our 3D models for the characters in the game. In the near future, we will be adding yet another mobile optimized engine, namely, the augmented reality engine. In this paper, we will present our work on object tracking and 3D modeling for Pico Life and contrast the performances of the two engines on three different mobile platforms, namely, Texas Instruments' OMAP3630 (Motorola Droid X running Android Gingerbread), Qualcomm's MSM8660 Snapdragon (HTC Evo 3D running Android Gingerbread) and the Texas Instruments' OMAP4430 (Blaze Development platform running Android Gingerbread).
Real-Time Facial Expression Recognition on Smartphones

Temporal segmentation of real time video is an important part for automatic facial expression recognition system. Many studies for facial expression recognition have been carried out under restricted experimental environment such as pre-segmented video set. In this paper, we present a real-time temporal video segmenting approach for automatic facial expression recognition applicable in a smartphone. The proposed system uses a Finite State Machine (FSM) for segmenting real time video into temporal phases from neutral expression to the peak of an expression. The FSM uses Lucas-Kanade's optical flow vector based scores for state transitions to adapt the varying speeds of facial expressions. While even HMM based or hybrid HMM model based approaches handling time series data require sampling times, the proposed system runs without any sampling time delay. The proposed system performs facial expression recognition with Support Vector Machines (SVM) on every apex state after automatic temporal segmentation. The mobile app with our approach runs on Samsung Galaxy S3 with 3.7 fps and the accuracy of real-time mobile emotion recognition is about 70.6% for 6 basic emotions by 5 subjects who are not professional actors.
Robot swarm communication networks: Architectures, protocols, and applications

There have been increasing interests in deploying a team of robots, or robot swarms, to fulfill certain complicated tasks such as surveillance. Since robot swarms may move to areas of far distance, it is important to have a pervasive networking environment for communications among robots, administrators, and mobile users. For this purpose, we propose to build a wireless mesh network as the wireless backbone within the areas of special interest. One or more robots can get connected with a nearby mesh router and access the remote server. Within each swarm, a self-organizing mobile ad hoc network is formed. With this type of robot swarm communication network, there are many important open issues to be addressed.
Association rule mining in multiple, multidimensional time series medical data

Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associated with different quantitative attributes, they form a multiple multi-dimensional framework. In this paper, we consider real-life time series data of muscular activities of human participants obtained from multiple Electromyogram (EMG) sensors and discover patterns in these EMG data streams.
Demonstration abstract: Upper body motion capture system using inertial sensors

Motion capture plays an important role in interactive gaming, animation, film industry and navigation. The existing camera-based motion capture studios are expensive and require a clear line of sight; hence they cannot be applied to ubiquitous applications. With the rapid development of low-cost MEMS sensors and sensor fusion techniques, the inertial sensor based motion capture systems are attracting a lot of attention because of the seamless deployment, low system cost and the comparable accuracy they provide. In this paper, we demonstrate a wireless real-time inertial motion capture system.
Calculating Patient Similarity Based on Respiration Induced Tumor Motion

In stereo tactic radiotherapy for thoracic and abdominal tumors, respiratory motion management is crucial for improving efficacy of treatment, while minimizing risk to heathy tissue and organs. Since tumor motion exhibits dynamic variation in characteristics, analyzing the behavior distribution of tumor motion can improve treatment planning. Identifying similarities among patients is an intuitive step towards patient profiling for optimal treatment strategy. This paper investigates how patients, undergoing radiotherapy, can be clustered into five treatment groups, which are identified by medical physicists. And in order to do so, we propose a combination of an adaptive segmentation technique and couple it with a set wise clustering approach for measuring similarity between patients. Our methods aim to group the patients solely based on their tumor motion traces brought about by respiration. Through a series of empirical and statistical analyses, we explore the impact of different feature sets and processing methodologies on the proposed patient grouping approach.
Real-Time Mobile Facial Expression Recognition System -- A Case Study

This paper presents a mobile application for real time facial expression recognition running on a smart phone with a camera. The proposed system uses a set of Support Vector Machines (SVMs) for classifying 6 basic emotions and neutral expression along with checking mouth status. The facial expression features for emotion recognition are extracted by Active Shape Model (ASM) fitting landmarks on a face and then dynamic features are generated by the displacement between neutral and expression features. We show experimental results with 86% of accuracy with 10 folds cross validation in 309 video samples of the extended Cohn-Kanade (CK+) dataset. Using the same SVM models, the mobile app is running on Samsung Galaxy S3 with 2.4 fps. The accuracy of real-time mobile emotion recognition is about 72% for 6 posed basic emotions and neutral expression by 7 subjects who are not professional actors.
Network Adaptive Textured Mesh Generation for Collaborative 3D Tele-Immersion

3D Tele-Immersion (3DTI) has emerged as an efficient environment for virtual interactions and collaborations in a variety of fields like rehabilitation, education, gaming, etc. In 3DTI, geographically distributed users are captured using multiple cameras and immersed in a single virtual environment. The quality of experience depends on the available network bandwidth, quality of the 3D model generated and the time taken for rendering. In a collaborative environment, achieving high quality, high frame rate rendering by transmitting data to multiple sites having different bandwidth is challenging. In this paper we introduce a network adaptive textured mesh generation scheme to transmit varying quality data based on the available bandwidth. To reduce the volume of information transmitted, a visual quality based vertex selection approach is used to generate a sparse representation of the user. This sparse representation is then transmitted to the receiver side where a sweep-line based technique is used to generate a 3D mesh of the user. High visual quality is maintained by transmitting a high resolution texture image compressed using a lossy compression algorithm. In our studies users were unable to notice visual quality variations of the rendered 3D model even at 90% compression.
End-to-end framework for QoS guarantee in heterogeneous wired-cum-wireless networks

With information access becoming more and more ubiquitous, there is a need for providing QoS support for communication that spans wired and wireless networks. For the wired side, RSVP/SBM has been widely accepted as a flow reservation scheme in IEEE 802 style LANs. In this paper, we investigate the integration of RSVP and a RSVP-like flow reservation scheme in wireless LANs, as an end-to-end solution for QoS guarantee in wired-cum-wireless networks. We propose WRESV, an RSVP-like flow reservation and admission control scheme for IEEE 802.11 wireless LAN. Using WRESV, wired/wireless integration can be easily implemented by cross-layer interaction at the access point. Main components of the integration are RSVP-WRESV parameter mapping, and the initiation of new reservation messages, depending on where senders/receivers are located. In addition, we also propose various optimizations for supporting multicast session, mobility management, and admission control.
SAMHIS: A Robust Motion Space for Human Activity Recognition

In recent years, many local descriptor based approaches have been proposed for human activity recognition, which perform well on challenging datasets. However, most of these approaches are computationally intensive, extract irrelevant background features and fail to capture global temporal information. We propose to overcome these issues by introducing a compact and robust motion space that can be used to extract both spatial and temporal aspects of activities using local descriptors. We present Speed Adapted Motion History Image Space (SAMHIS) that employs a variant of Motion History Image for representing motion. This space alleviates both self-occlusion as well as the speed-related issues associated with different kinds of motion. We go on to show using a standard bag of visual words model that extracting appearance based local descriptors from this space is very effective for recognizing activity. Our approach yields promising results on the KTH and Weizmann dataset.
Robust Blind Watermarking of Point-Sampled Geometry

Digital watermarking for copyright protection of 3-D meshes cannot be directly applied to point clouds, since we need to derive consistent connectivity information, which might change due to attacks, such as noise addition and cropping. Schemes for point clouds operate only on the geometric data and, hence, are generic and applicable to mesh-based representations of 3-D models. For building generic copyright schemes for 3-D models, this paper presents a robust blind watermarking mechanism for 3-D point-sampled geometry. The basic idea is to find a cluster tree from clusters of 3-D points. Using the cluster tree, watermarks can be embedded and extracted by deriving an order among points at global (intracluster) and local levels (intercluster). The multiple bit watermarks are encoded/decoded inside each cluster based on an extension of the cluster structure-based 3-D quantization index modulation. The encoding mechanism makes the technique robust against uniform affine transformations (rotation, scaling, and transformation), reordering, cropping, simplification, and noise addition attacks. The technique when applied to 3-D meshes also achieves robustness against retriangulation and progressive compression techniques. Customization of the bit-encoding scheme achieves high hiding capacity with embedding rates that are equal to 4 b/point, while maintaining the imperceptibility of the watermark with low distortions. The estimated time complexity is O (n logn), where n is the number of 3-D points.
Point-Based Manifold Harmonics

This paper proposes an algorithm to build a set of orthogonal Point-Based Manifold Harmonic Bases (PB-MHB) for spectral analysis over point-sampled manifold surfaces. To ensure that PB-MHB are orthogonal to each other, it is necessary to have symmetrizable discrete Laplace-Beltrami Operator (LBO) over the surfaces. Existing converging discrete LBO for point clouds, as proposed by Belkin et al. [CHECK END OF SENTENCE], is not guaranteed to be symmetrizable. We build a new point-wisely discrete LBO over the point-sampled surface that is guaranteed to be symmetrizable, and prove its convergence. By solving the eigen problem related to the new operator, we define a set of orthogonal bases over the point cloud. Experiments show that the new operator is converging better than other symmetrizable discrete Laplacian operators (such as graph Laplacian) defined on point-sampled surfaces, and can provide orthogonal bases for further spectral geometric analysis and processing tasks.
On supporting collaborative haptic interactions with physically-based 3D deformations

Haptic-enabled collaborative systems have long been limited to 3D rigid models only, primarily due to slow force calculations, long-time deformable simulations and large communication loads. In this paper, we propose a novel system to support real-time sharing of haptic feedbacks and deformable simulations of physically-based 3D models in a distributed virtual environment. Particularly, adopting a spectral method, we can effectively complete force calculation and deformable simulation based on user manipulations so as to achieve real-time streaming with low network loads. In addition, we explain how our system works under two different collaborative network architectures, and analyze them separately. The experimental results confirm the validity of our approach and prove its effectiveness. Our research has a wide range of applications in such fields as education (e.g., distributed, virtual class rooms) and entertainment (e.g., gaming).
Multimedia Retrieval Conference Enjoys Texas Hospitality

The Third ACM International Conference on Multimedia Retrieval (ICMR) was held in Dallas, Texas, from 16-19 April 2013. The conference aims to promote intellectual exchanges and interactions among scientists, engineers, students, multimedia researchers in academia as well as industry through various programs and events. The year's ACM ICMR included a keynote address by Mor Naaman of Rutgers University on &#x0022;Time for Events, and the Future of (Social) Multimedia,&#x0022; a panel entitled &#x0022;Recommendation Systems Have Taken Control: Is Multimedia Retrieval Still Relevant?&#x0022; and a new doctoral symposium event.