nils-herrmann/clean_scirepeval huggingface dataset:
A real time, distributed system with haptic interfaces for fine motor skill rehabilitation and its quality of experience

Recent inclusion of haptics in rehabilitation is expanding and this requires efficient architecture for stable and synchronized operation. In this paper, we propose a distributed architecture with multiple haptic interfaces to improve the fine motor skill disability. The preceding works with haptics for rehabilitation and motor recovery practices a stand alone infrastructure with time consuming operations for training. Compared with the existing methods, the proposed system provides three significant contributions: (i) a real time 3-phase operation to avoid invariable and time consuming practice with recorded exercises; (ii) a distributed environment to support one-to-many remote accessibility for training and practice; (iii) a novel force rendering algorithm to handle better synchronization among the haptic interfaces in the network to provide smooth force feedback in real time. The effectiveness of our system is demonstrated by the user study that also includes the evaluation from a specialist.
An Integrated Mobile Wireless System for Capturing Physiological Data Streams during a Cognitive-motor Task: Applications for Aging

Cognitive, motor and perceptual processes diminish with age and thus limit adaptive capabilities of older individuals. Our hypothesis is that with aging there is decreased expression of these proactive adaptive capabilities. These experiments were designed to test this hypothesis by implementing an integrated approach to quantifying physiological characteristics in older individuals. We are working towards building an integrated wireless motion capture and physiological data monitoring system to quantify and data mine various physiologic and motoric streams in a controlled experimental environment. In this paper, synchronized motion capture and EMG data was obtained in young and old subjects performing a cognitive-motor task. We show that some, but not all baseline measures were significantly different in older compared to young subjects. Quantification of these baseline measures will allow us to develop new experimental paradigms that compensate for age-related decline in motor control, sensation, and cognition through brain- plasticity targeted training in rich learning environments.
Experiences with Multi-modal Collaborative Virtual Laboratory (MMCVL)

Training through Multi-modal Collaborative Virtual Laboratory (MMCVL) aims at developing or improving skills of students without the need of them being physically present. MMCVL addresses the problems faced by the current education system such as lack of resources and safe use of expensive laboratory equipment. It also provides a means for easy collaboration between students and teachers from different universities and schools. Multimedia data in terms of 3D mesh, skeleton, audio and virtual object physics interaction are incorporated in MMCVL to provide a 3D Tele-Immersion environment. The system uses low-cost RGB-D cameras such as Microsoft Kinect V2 to capture and generate 3D model of the person by extracting him/her from the entire captured data and immersing it in different interactive virtual environments. Different lab environments can be virtually created to provide for and replace the real laboratories. Object interactions allow for users to interact with the virtual objects present in the scene similar to real lab setup. Recording module of the toolkit allows future reference for training and testing of the student. The system also facilitates virtual feedback by giving the correct measurements, video demonstrations as well as audio communication with the collaborating teacher. Two different Chemistry experiments were performed to evaluate the user experience and usability aspects of MMCVL. Results obtained from the user study analysis prove the system to be fun and realistic, and at the same time engaging and motivating for learning laboratory experiments.
Streaming 3D shape deformations in collaborative virtual environment

Collaborative virtual environment has been limited on static or rigid 3D models, due to the difficulties of real-time streaming of large amounts of data that is required to describe motions of 3D deformable models. Streaming shape deformations of complex 3D models arising from a remote user's manipulations is a challenging task. In this paper, we present a framework based on spectral transformation that encodes surface deformations in a frequency format to successfully meet the challenge, and demonstrate its use in a distributed virtual environment. Our research contributions through this framework include: i) we reduce the data size to be streamed for surface deformations since we stream only the transformed spectral coefficients and not the deformed model; ii) we propose a mapping method to allow models with multi-resolutions to have the same deformations simultaneously; iii) our streaming strategy can tolerate loss without the need for special handling of packet loss. Our system guarantees real-time transmission of shape deformations and ensures the smooth motions of 3D models. Moreover, we achieve very effective performance over real Internet conditions as well as a local LAN. Experimental results show that we get low distortion and small delays even when surface deformations of large and complicated 3D models are streamed over lossy networks.
QOAR: Adaptive QoS Scheme in Multi-Rate Wireless LANs

With the availability of multiple rates in IEEE 802.11 a/b/g wireless LANs, it is desirable to improve the network capacity and temporal fairness by sending multiple consecutive frames over high rate links, as proposed in opportunistic auto rate (OAR ). However, the basic OAR does not provide quality of service (QoS) guarantee and thus is not sufficient in supporting real time voice/video traffic. In this paper, we further enhance the OAR protocol with a set of QoS mechanisms. The proposed QOAR protocol consists of two protocols: (i) a traffic- differentiating flow weight adaptation protocol (FWA) that dynamically tunes both contention window and concatenation number per channel access; (ii) an admission control protocol (AC) that guarantees the bandwidth/delay requirements of multimedia services. Extensive simulation studies show that QOAR enables QoS for real-time traffic yet maximizes performance of best effort traffic.
Data Hiding based Compression Mechanism for 3D Models

Different compression methods (Jingliang Peng et al., 2005) such as progressive meshes and single refinement mesh compression exist for mesh representation for 3D models and improving them is a challenge. This paper is a step in this direction, where we show that data hiding methods can be used to significantly improve the compression achieved for such methods. 3D meshes are made up of connectivity (edge set E) and geometric (vertices set V) information. The data hiding method should provide a very high embedding rate in order to achieve a desirable compression ratio. This can be modeled mathematically, given 'V points or vertices in 3D space; for a given compression ratio we use 'AT' points and hide rest of the connectivity and geometric information inside it. These points are termed as the encoding points and the encoded information is termed is the compressed information.
Haptic simulation of needle-tissue interaction based on shape matching

Simulating needle-tissue interaction in a haptic-enabled environment is an essential component in many virtual surgical training procedures, where the trainee would practice needle insertion and retraction repeatedly. Efficiency and stability are of major importance for the corresponding visual and haptic rendering. In this paper, we present a novel system for a real-time and robust simulation of needle-tissue interaction with haptic devices. The soft tissue is modeled using the classic shape matching method for its excellent numerical stability. It can interact with a one dimensional inextensible rigid/flexible virtual needle freely. The feedback force from the needle is formulated as the gradient of the potential energy of the soft tissue based on particle constraint. Under the framework of shape matching, the feedback force can be efficiently evaluated and smoothly rendered through haptic devices. Our model can also support various material properties so that tissues of different stiffness can be well handled.
MAC protocol enhancements for QoS guarantee and fairness over the IEEE 802.11 wireless LANs

In future wireless networks, different traffic classes will exhibit a large variety of characteristics and QoS requirements, such as transmission rate, maximum tolerable bit error rate and timeout specifications. However, currently there is no standard way of guaranteeing QoS in wireless access networks like wireless LAN based on IEEE 802.11. In this paper, we propose medium access control protocol enhancements and a distributed scheduler for QoS guarantees and fairness over IEEE 802.11 WLAN. The proposed scheme uses distributed scheduling at both the access point and the user terminals to schedule the transmission of packets according to their delay requirements. The algorithms used for both scheduling are the same. A flexible and fair resource allocation method among the traffic classes and the user terminals is provided by this scheme. Its performance has been evaluated using the UCB/LBNL/VINT Network Simulator and an implementation in the Linux kernel.
The randomized approximating graph algorithm for image annotation refinement problem

Recently, images on the Web and personal computers are prevalent around the humanpsilas life. To retrieve effectively those images, there are many AIA (Automatic Image Annotation) algorithms. However, it still suffers from low-level accuracy since it couldnpsilat overcome the semantic-gap be tween low-level features (dasiacolorpsila,dasiatexturepsila and dasiashapepsila) and high-level semantic meanings (e.g., dasiaskypsila,dasiabeachpsila). Namely, AIA techniques annotates images with many noisy key words. Refinement process has been appeared in these days and it tries to remove noisy keywords by using Knowledge-base and boosting candidate keywords. Because of limitless of candidate keywords and the incorrectness of web-image textual descriptions, this is the time we need to have deterministic polynomial time algorithm. We show that finding optimal solution for removing noisy keywords in the graph is NP-Complete problem and propose new methodology for KBIAR (Knowledge Based Image Annotation Refinement) using the randomized approximation graph algorithm as the general deterministic polynomial time algorithm.
Content Based 3D Human Document Retrieval Using Latent Semantic Mapping

There has been an enormous increase of 3D human motion data in various fields, such as 3D gaming (such an EA sports) and medical fields (physical medicine and rehabilitations). We need an effective content-based 3D human motion retrieval scheme supporting human-level language queries. However, there is a big semantic gap between these two media since the 3D Human motion data and text are heterogeneous forms. In this paper, we propose a cross-media retrieval framework that reduces the semantic gap by semantic spatiotemporal dimensional reduction and reformulates 3D human motion data to HMDoc (Human Motion Document) representation, which is quite applicable for a traditional information retrieval technique such as Latent Semantic Indexing. After mapping complex 3D human motion matrix data into semantic space, we can achieve 88.72% precision, 86.98% recall accuracy with 14 different motion categories that consists of 370, 294 frames. Our proposed approach (HMDoc) extracts the semantic characteristics of human motion capture data. This semantic feature compact representation outperformed other works such as weighted motion feature vector and LB_KEOGH's method, Geometric feature representation.
Blind invisible watermarking for 3D meshes with textures

We propose to embed watermarks by modifying the texture mapping information of 3D models rather than modifying the geometry information or texture image as existing works do. We present a blind watermarking method based on spectral decomposition that incorporates the process of Texture Image Compensation (TIC) which ensures no visual distortion. We describe a Neighbor Couple Embedding (NCE) scheme that works on the Manifold Harmonics Transform (MHT) of the texture coordinate functions. Experiments show that this method is robust against common attacks such as adding noise attacks, uniform affine transformation attacks, local modification attacks and produces no visual distortion on the rendered 3D models. Our contributions include watermarking the texture mapping information with no visual distortion as well as a novel embedding method that is robust against various possible attacks.
On Lagrange multiplier and quantizer adjustment for H.264 frame-layer video rate control

H.264/AVC encoder employs a complex mode-decision technique based on rate-distortion optimization. It calculates rate-distortion cost (RDcost) for all possible modes to choose the best one having the minimum RDcost. This paper presents a frame-layer rate control for H.264/AVC that computes the Lagrange multiplier (/spl lambda//sub MODE/) for mode decision by using a quantization parameter (QP) which may be different from that used for encoding. At the same time, we also compare actual bits produced by previous macroblocks (MBs) with the total bits allocated to these MBs to further modify /spl lambda//sub MODE/. The objective of these measures aims to produce bits as close to the frame target bits for rate control as possible. This is very important in the case of low-bit-rate tight buffer applications. In order to obtain an accurate QP for a frame, we employ a complexity-based bit-allocation scheme and a QP adjustment method. Simulation results comparing with the H.264 Joint Video Team (JVT) rate control method show that the H.264 encoder, using the proposed algorithm, achieves a visual quality improvement of about 0.56 dB, performs better for buffer overflow and underflow, and achieves a smaller PSNR deviation.
Rapid block-matching motion estimation using modified diamond search algorithm

Due to the considerable computational complexity of full-search (ITS) in motion estimation, many suboptimal but fast block-matching algorithms (BMAs) have been developed. Among them, the diamond search (DS) series is the most promising method. To further reduce complexity and improve performance, we propose a modified diamond-search (MODS) algorithm for rapid block matching based on the well-known DS algorithm. A novel fine granularity halfway-stop (FGHS) method based on a dynamic block distortion threshold is also proposed. To avoid being trapped in local optima, unlike some small DS methods, MODS adaptively starts with a relatively large search pattern for high motion blocks which are automatically determined via the first block matching distortion. The threshold is obtained via a linear model utilizing already computed distortion statistics. Experiments show that the proposed algorithm achieves less search points with no significant PSNR degradation when compared to that of FS and other fast BMAs.
Depth-Preserving Stereo Image Retargeting Based on Pixel Fusion

In this paper, we propose a pixel fusion-based stereo image retargeting method, which could adaptively retarget stereo images with flexible aspect ratios, simultaneously preserving the depth. Retargeting each image independently by the pixel fusion method ignores the disparity relationship between pixels in the image pair and hence will introduce the distortion of disparity. To address this issue, we advocate to extend the single pixel fusion-based way to be applicable for stereo image pair. First, seams are selected based on the energy function, which simultaneously considers the seam selecting and seam matching. Second, a seam-matching-based matching map is proposed to preserve the disparity relationship between image pair. Then, the scaling factors for the left image are assigned considering both the important object and depth preservation. Subsequently, the scaling factors for the right image are obtained according to the proposed matching map. Based on these scaling factors, the stereo image pair is retargeted with pixel fusion. In contrast to removing pixels to resize image, the way of pixel fusion can obtain more smooth results with less depth distortion. Experimental results demonstrate that our method achieves more preferable qualities in both depth and shape preservation for stereo image retargeting.
Simplified depth intra mode selection for 3D video compression

A simplified depth modeling mode (DMM) selection algorithm is proposed for 3D-HEVC depth intra coding. Since DMMs are designed for coding units (CUs) with edge or sharp transition, it is not efficient for smooth CU compression. Based on the observation that most CUs in a depth frame are smooth or flat, we notice most of the DMM full-Rate-Distortion (RD) search could be skipped. Using the modes in full-RD list as the skip signal, we propose a simplified DMM selection algorithm to avoid unnecessary DMM full-RD cost calculation. Since modes in full-RD list already exist, we can derive the skip signal without any additional calculation. The test result for the proposed simplified selection algorithm shows 21.8% encoding time saving with only 0.16% bitrate increasing in coded and synthesized view for All-Intra test case.
Low-delay rate control for real-time H.264/AVC video coding

This paper presents an efficient rate control scheme for the H.264/AVC video coding in low-delay environments. In our scheme, we propose an enhancement to the buffer-status based H.264/AVC bit allocation method. The enhancement is by using a PSNR-based frame complexity estimation to improve the existing mean absolute difference based (MAD-based) complexity measure. Bit allocation to each frame is not just computed by encoder buffer status but also adjusted by a combined frame complexity measure. To prevent the buffer from undesirable overflow or underflow under small buffer size constraint in low delay environment,the computed quantization parameter (QP) for the current MB is adjusted based on actual encoding results at that point. We also propose to compare the bits produced by each mode with the average target bits per MB to dynamically modify Lagrange multiplier (/spl lambda//sub MODE/) for mode decision. The objective of QP and /spl lambda//sub MODE/ adjustment is to produce bits as close to the frame target as possible, which is especially important for low delay applications. Simulation results show that the H.264 coder, using our proposed scheme, obtains significant improvement for the mismatch ratio of target bits and actual bits in all testing cases, achieves a visual quality improvement of about 0.6 dB on the average, performs better for buffer overflow and underflow,and achieves a similar or smaller PSNR deviation.
An integrated system architecture for binary image understanding

The authors take a holistic approach to developing a system level architecture for the problem of image capture and understanding in binary images. It includes a direct method of image capture that removes many of the I/O bottlenecks inherent in other systems. It also cooperates with an adaptive focusing mechanism in order to be able to provide quickly and efficiently a higher resolution image for a sub-area of the total scene whenever foveal attention is required, which would need considerable overhead in most systems thereby precluding real-time behavior. The architecture supports all the three levels of vision processing (low, intermediate, and high) for real time object recognition in binary images by providing parallel mesh connected simple processors (PEs) for low level processing as well as a hierarchy of successively powerful PEs providing a pyramidal type of structure for higher levels of processing. It is also shown that this can be efficiently implemented as a dense and regular single or multiple VLSI chips making possible direct mounting of the system inside a camera. On the processor (PE) level the authors have added enhancements over previous architectures that make it possible to form a fast and economical image understanding system for all three levels of processing for binary images. The main contribution has been the generally broad system level approach of active vision to the development of the architecture and the three enhancements to the PEs which include a switchbox mechanism for extending the local connectivity to establish communications between nonlocal neighbors, a hardware implementation of an artificial neural network that provides direct support for connectionist processing, and an embedded multilevel pyramid with successively powerful PEs. This is shown to fulfill the processing requirements for real-time binary image understanding applications.
A Theoretical Model and Study of Weighted MCTF Residual Energy

This paper presents a theoretical model and study of the impact of the weighted motion-compensated residual energy on the coding efficiency of motion-compensated temporal filtering (MCTF) when MCTF update steps are performed at both encoder and decoder sides and when update steps are executed at the encoder side only. We observe that in the presence of the uncompensated quantization errors due to the MCTF open-loop structure, the decoder must attempt to recover the update weight used by the encoder and this non-linear transform may contribute to the possible magnification of the quantization errors. We apply our analysis to the joint scalable video model (JSVM) 2.0. It is demonstrated that performing the MCTF update step at the decoder side does not contribute significantly to the coding efficiency, except at high spatial-temporal resolutions with high bit rates. This further justifies theoretically the elimination of the MCTF update step as a normative tool for temporal scalability in the current H.264/AVC scalable extension development
Inductive techniques for formal verification of systolic array designs in DSP applications

It is shown how several inductive techniques can be utilized to provide fast and efficient proofs to the correctness of systolic designs in digital signal processing (DSP) applications. These techniques exploit the repeatability, regularity, and locality nature of systolic arrays and algorithms in DSP to produce fast proofs independent of the array size. How inductive techniques can be applied to different array topologies suitable for DSP is also shown, and the structure of the verifier developed to automate induction using logic programming is illustrated.<<ETX>>
A new modeling for visual attention calculation in video coding

To make effective use of video coding bit-steam and support sufficiently high subjective QoE(Quality of Experience), we propose a ROIs (Regions of Interest) detection model based on current achievements of psychology and visual attention. Combined with saliency calculation and eye-movement tracking analysis, the modeling can obtain the ROIs of different viewing duration. According to the ROIs, method of rate adaptation in video is proposed. Through some experiments, we show that our method can improve subjective QoE and bring significant improvement in ROI areas.