nils-herrmann/clean_scirepeval huggingface dataset:
Improved refinement search for H.263 to H.264/AVC transcoding based on the minimum cost tendency search

An improved refinement search method for transcoding from H.263 to H.264/AVC is proposed in this paper. Many existing motion re-estimation methods refine the input motion vector (MV) with a small search range, which is usually input MV biased. Motion estimation (ME) in H.263 usually does not consider the rate required for coding the MV, and hence, the input MV may incur a large cost in H.264/AVC. To overcome this problem, we introduce a refinement search method, called minimum cost tendency search (MCTS), which takes the difference between the cost functions for ME in H.263 and H.264/AVC into consideration. The input MV and the predictor MV are used as two anchor points. The proposed MCTS starts searching from the anchor point with a higher cost to another. Finally, the best point is chosen as the center for further refinement. The performance of MCTS is evaluated by comparing with full search, FME in JM software and refinement scheme using small diamond pattern around the input MV (RSD). Experimental results show the proposed MCTS performs more stable than FME and RSD over a wide range of output video quality
3-D Motion Estimation for Visual Saliency Modeling

Visual saliency is a probabilistic estimate of how likely a spatial area in an image or video frame is to attract human visual attention relative to other areas. When existing bottom-up saliency models aggregate low-level features to construct a plausible saliency map, only 2-D motion cues are used as motion features, even though videos typically capture dynamic 3-D scenes. In this paper, we introduce 3-D motion into bottom-up saliency modeling for texture-plus-depth videos. We first propose an efficient 3-D motion estimation algorithm, which computes a 3-D motion vector (3DMV) for each sub-block in the frame. Using the computed 3DMVs, we then derive several saliency channels (called 3DMV channels), which are incorporated into a bottom-up saliency model to obtain enhanced saliency maps. Experiments tracking human gaze show that incorporating our 3DMV channels into bottom-up saliency model significantly improves the accuracy of derived saliency maps.
An improved fast feature-based block motion estimation

A fast block matching algorithm in the feature domain was proposed by Fok and Au (1993) which achieves a computation reduction factor of N/2 with search block size of N/spl times/N. This paper presents an improved fast block matching algorithm in the integral projections feature domain. This algorithm is based on the fast block matching algorithm in the feature domain and a new motion field sub-sampling scheme. By utilizing the properties of the features and the motion field sub-sampling scheme, with a search block size of N/spl times/N, the improved algorithm can achieve a computation reduction factor of N while retaining close-to-optimal performance in the mean absolute difference (MAD) sense.<<ETX>>
Dot Scissor: A Single-Click Interface for Mesh Segmentation

This paper presents a very easy-to-use interactive tool, which we call dot scissor, for mesh segmentation. The user's effort is reduced to placing only a single click where a cut is desired. Such a simple interface is made possible by a directional search strategy supported by a concavity-aware harmonic field and a robust voting scheme that selects the best isoline as the cut. With a concavity-aware weighting scheme, the harmonic fields gather dense isolines along concave regions which are natural boundaries of semantic components. The voting scheme relies on an isoline-face scoring mechanism that considers both shape geometry and user intent. We show by extensive experiments and quantitative analysis that our tool advances the state-of-the-art segmentation methods in both simplicity of use and segmentation quality.
Two-level optimized tone mapping for high dynamic range images

In this paper, we propose a two-step tone-mapping algorithm to convert a high dynamic range (HDR) image to a low dynamic range (LDR) image. The first step S1 constructs a global tone mapping which optimizes between uniform quantization and histogram equalization. The second step S2 improves the visual quality by optimizing between global operation and local contrast maintenance. Both S1 and S2 can operate independent of each other. Simulation results suggest that proposed tone mapping algorithm can give good visual quality, with S1+S2 better than S1 alone. Simulation results also suggest that proposed S2 can be combined with other existing tone mapping methods to achieve improved local contrast.
Fast Multi-Hypothesis Motion Compensated Filter for Video Denoising

Multi-hypothesis motion compensated filter (MHMCF) utilizes a number of hypotheses (temporal predictions) to estimate the current pixel which is corrupted with noise. While showing remarkable denoising results, MHMCF is computationally intensive as full search is employed in the expectation of finding good temporal predictions in the presence of noise. In the frame of MHMCF, a fast denoising algorithm FMHMCF is proposed in this paper. With edge preserved low pass prefiltering and noise-robust fast multihypothesis search, FMHMCF could find reliable hypotheses while checking very few search locations, so that the denoising process can be dramatically accelerated. Experimental results show that FM-HMCF can be 10 to 15 times faster than MHMCF, while achieving the same or even better denoising performance.
Optimizing the MPEG-4 encoder-advanced diamond zonal search

Motion estimation (ME) is an important part of the MPEG-4 encoder, due to its significant impact on the bitrate and the output quality of the encoded sequence. Unfortunately this feature occupies a significant part of the encoding time especially when using the straightforward full search (FS) algorithm. The diamond search (DS) was recently accepted as a fast motion estimation algorithm for the MPEG-4 VM. In this paper we propose a new algorithm named advanced diamond zonal search (ADZS), which is significantly faster than DS (in terms of number of checking points and total encoding time) and gives similar, if not better, quality (in terms of PSNR) of the output sequence. This is more obvious in the high bit rate cases. Our experiments verify the superiority of the proposed algorithm.
Spatio-temporal boundary matching algorithm for temporal error concealment

In this paper, a novel temporal error concealment algorithm, called spatio-temporal boundary matching algorithm (STBMA), is proposed to recover the information lost in the video transmission. Different from the classical boundary matching algorithm (BMA), which just considers the spatial smoothness property, the proposed algorithm introduces a new distortion function to exploit both the spatial and temporal smoothness properties to recover the lost motion vector (MV) from candidates. The new distortion function involves two terms: spatial distortion term and temporal distortion term. Since both the spatial and temporal smoothness properties are involved, the proposed method can better minimize the distortion of the recovered block and recover more accurate MV. The proposed algorithm has been tested on H.264 reference software JM 9.0. The experimental results demonstrate the proposed algorithm can obtain better PSNR performance and visual quality, compared with BMA which is adopted in H.264
Scalable coding of stream cipher encrypted images via adaptive sampling

This work proposes a novel scalable image compression method for stream cipher encrypted images. The bit stream in the base layer is produced by coding a series of non-overlapping patches of the uniformly down-sampled version of the encrypted image. An off-line learning approach can be exploited to model the reconstruction error of original image patch based on the intrinsic relationship between the local complexity and the length of the compressed bit stream. This error model leads to a greedy strategy of adaptively selecting pixels to be coded in the enhancement layer. At the decoder side, an iterative, multi-scale technique is developed to reconstruct the image from available pixel samples. Experimental results demonstrate that the proposed scheme outperforms the state-of-the-art in terms of rate-distortion (RD) performance at low and medium rate regions.
Bilateral Normal Filtering for Mesh Denoising

Decoupling local geometric features from the spatial location of a mesh is crucial for feature-preserving mesh denoising. This paper focuses on first order features, i.e., facet normals, and presents a simple yet effective anisotropic mesh denoising framework via normal field denoising. Unlike previous denoising methods based on normal filtering, which process normals defined on the Gauss sphere, our method considers normals as a surface signal defined over the original mesh. This allows the design of a novel bilateral normal filter that depends on both spatial distance and signal distance. Our bilateral filter is a more natural extension of the elegant bilateral filter for image denoising than those used in previous bilateral mesh denoising methods. Besides applying this bilateral normal filter in a local, iterative scheme, as common in most of previous works, we present for the first time a global, noniterative scheme for an isotropic denoising. We show that the former scheme is faster and more effective for denoising extremely noisy meshes while the latter scheme is more robust to irregular surface sampling. We demonstrate that both our feature-preserving schemes generally produce visually and numerically better denoising results than previous methods, especially at challenging regions with sharp features or irregular sampling.
Joint forward backward error concealment of redundantly coded video

Error concealment at the video decoder is to recover erroneous picture region based on correctly decoded region in the same frame or the neighboring frames. However, the existing error concealment methods cannot give satisfactory result in some situations, e.g. when a whole frame is lost. In this paper, we propose a novel joint forward-backward concealment (JFBC) method. The key observation is that, a future frame can be recovered without using its reference frame when some error resilience tools, such as redundant picture, are used. Based on this observation, the proposed JFBC performs temporal error concealment along not only forward direction but also backward direction. Furthermore, the JFBC combines the forward concealment result and the backward concealment result by using linear minimum mean square error (LMMSE) estimation. The JFBC estimates for each pixel an error level such that the weights in LMMSE estimation are adaptive in pixel-level. In the experiments, the JFBC achieves considerable gain over the state-of-the-art temporal error concealment method.
A content adaptive de-interlacing algorithm [video signal processing applications]

This paper proposed a content adaptive de-interlacing algorithm (CADI) for conversion of interlaced video to progressive video. The proposed CADI algorithm interpolates the missing field based on the local image characteristics (smooth, horizontal edge, vertical edge and texture) and chooses the most appropriate de-interlacing algorithm. In addition, a novel vector matching algorithm is introduced for interpolating missing pixels in the horizontal edge region. It has three features to increase the accuracy of estimating edge directions: an adaptive search range for different edge orientations, combining consecutive pixels for directional correlation estimation within the same edge region and consistency checking along the candidate directions. Experimental results show that the proposed CADI algorithm outperforms existing algorithms in various video sequences, and produces high quality de-interlaced frames.
Fast control grid point estimation for mesh based motion estimation

In this paper, a fast algorithm is proposed for mesh based motion estimation. Mesh based motion estimation provides a smooth motion field and better visual quality than the block based method in the sense that it would not produce blocking artifacts. However, the search of optimal grid point locations in mesh based motion estimation is very slow by the fact that it needs a lot of interpolations and iteration during the search. The proposed fast algorithm utilizes a block-based algorithm, which is much faster, in the search of the optimal location of grid points. A varying search block size approach is proposed to use during iteration. The current fast algorithm is proved to produce a comparable result as with the traditional mesh based motion estimation using exhaustive search.
Improved bidirectionally decodable Wyner-Ziv video coding

Reverse playback is one of the most common video cassette recording (VCR) functions for video streaming systems. However, the predictive processing techniques employed in traditional hybrid video coding schemes severely complicate the reverse-play operation. In this paper, we enhance our previously proposed bidirectionally decodable Wyner-Ziv video coding scheme which supports both forward decoding and backward decoding. We derive that in our scheme the optimal Lagrangian multiplier for the backward motion estimation should be averagely two times larger than for the forward motion estimation. The new multiplier contributes 0.2 dB gain in average. We propose an optimal P-frame/M-frame selection scheme to improve rate-distortion performance when the video is transmitted over error prone channels. The new scheme outperforms both H.264 and our previous scheme at all tested loss rate, and gain up to 0.55 dB over our previous scheme in low loss rate case.
Photo album compression By leveraging temporal-spatial correlations and HEVC

The advancing digital photography technology has resulted in a large number of photos stored in personal computers. Photo album compression algorithms aim to save storage space and efficiently manage photos. In this paper, a general forest structure model involving depth constrain for photo album compression is proposed, which further exploits the correlations between images in the photo album. We firstly represent the images as nodes in a graph and directed edges between them as predictive coding relationship. Affinity propagation is then applied to compute for a depth-constrained forest. Finally, we adopt depth-first search algorithm to generate the compression order according to forest structure and HEVC to compress the images with adaptive GOPs and reference list. Experimental results show that the proposed compression method provides much better rate-distortion performance compared to JPEG and significantly reduce the storage space.
Merge Frame Design for Video Stream Switching Using Piecewise Constant Functions.

The ability to efficiently switch from one pre-encoded video stream to another (e.g., for bitrate adaptation or view switching) is important for many interactive streaming applications. Recently, stream-switching mechanisms based on distributed source coding (DSC) have been proposed. In order to reduce the overall transmission rate, these approaches provide a merge mechanism, where information is sent to the decoder, such that the exact same frame can be reconstructed given that any one of a known set of side information (SI) frames is available at the decoder (e.g., each SI frame may correspond to a different stream from which we are switching). However, the use of bit-plane coding and channel coding in many DSC approaches leads to complex coding and decoding. In this paper, we propose an alternative approach for merging multiple SI frames, using a piecewise constant (PWC) function as the merge operator. In our approach, for each block to be reconstructed, a series of parameters of these PWC merge functions are transmitted in order to guarantee identical reconstruction given the known SI blocks. We consider two different scenarios. In the first case, a target frame is first given, and then merge parameters are chosen, so that this frame can be reconstructed exactly at the decoder. In contrast, in the second scenario, the reconstructed frame and the merge parameters are jointly optimized to meet a rate-distortion criteria. Experiments show that for both scenarios, our proposed merge techniques can outperform both a recent approach based on DSC and the SP-frame approach in H.264, in terms of compression efficiency and decoder complexity.
Motion vector fields based video coding

Motion vector fields (MVFs) are able to produce a more accurate prediction image than conventional block based motion compensation. However, MVFs are not used in conventional video coding standards due to the difficulty of efficient estimation and compression. In this work, we propose an MVF based video coding framework. We formulate the estimation of the MVF as a discrete optimization problem by both optimizing the residual energy and MVF smoothness, which can be efficiently solved by a graph cut algorithm with initialized motion vectors for each pixel. We then propose a modified rate distortion optimization approach for the MVF compression. Experimental results show that the proposed method has comparable performance in terms of object quality compared to the state-of-art of HEVC, while it has a better subjective performance by overcoming the block artifacts problem.
Image rectification for single camera stereo system

Single camera stereo system utilizes mirrors and a single camera for computational stereo, where the mirrors provide extra views needed for stereo and 3D reconstruction. In this paper, we investigate the basic epiploar geometric properties of the single camera stereo image and propose a novel image rectification technique to map the epipolar lines in the original image into the horizontally aligned lines in the rectified image. Besides, the rotation angles of the single camera corresponding to the planar mirror are derived during rectification. Experimental results show the robustness and accuracy of our method.
Precision enhancement of 3D surfaces from multiple quantized depth maps

Transmitting from sender compressed texture and depth maps of multiple viewpoints enables image synthesis at receiver from any intermediate virtual viewpoint via depth-image-based rendering (DIBR). We observe that quantized depth maps from different viewpoints of the same 3D scene constitutes multiple descriptions (MD) of the same signal, thus it is possible to reconstruct the 3D scene in higher precision at receiver when multiple depth maps are considered jointly. In this paper, we cast the precision enhancement of 3D surfaces from multiple quantized depth maps as a combinatorial optimization problem. First, we derive a lemma that allows us to increase the precision of a subset of 3D points with certainty, simply by discovering special intersections of quantization bins (QB) from both views. Then, we identify the most probable voxel-containing QB intersections using a shortest-path formulation. Experimental results show that our method can significantly increase the precision of decoded depth maps compared with standard decoding schemes.
Ray-space based camera spacing correction via convex optimization

3D technologies such like three-dimensional television and free viewpoint television have caught enormous attentions in the consumer market recently. However, because of the inaccurate camera configuration and environmental constraint, there are errors in the assumed equally-spaced camera intervals. In this paper, we propose a novel camera spacing correction algorithm to detect the spacing errors among the multiple cameras by making the corresponding points co-linear in the epipolar plane images. Experimental results show that the proposed algorithms are robust and can achieve good performance even if the corresponding pixels are not well detected. Meanwhile, our algorithm can be solved by convex optimization with an extremely low complexity.
Data hiding in halftone images by stochastic error diffusion

We propose a novel method called DHSED (data hiding stochastic error diffusion) to hide binary visual patterns in two error diffused halftone images. While one halftone image is only a regular error diffused image, stochastic error diffusion is applied to the other image to generate special stochastic characteristics with respect to the first image such that the visual pattern would appear when the two halftone images are overlaid Simulation results show that the two halftone images have good visual quality, and the hidden pattern appears with "normal" and "lower-than-normal" intensity when the two halftone images are overlaid.
Adaptive depth map filter for blocking artifacts removal and edge preserving

In depth map coding for 3D video coding systems, coding errors in edges can severely affect the synthesis quality. Edge errors mainly compose of two parts: one is blurring and ringing artifact around sharp edge and the other is fake edge caused by blocking artifact. In this paper, we propose an adaptive depth map filter to remove blocking artifacts while preserving depth edges. The proposed filter is designed based on bilateral filter, in which the range kernel parameter is changed adaptively considering the strength of edges and blocking artifacts. Experimental results demonstrate that the proposed depth map filter can achieve up to 0.41 dB gain on the synthesis quality compared to the deblocking filter in MVC at low bit rate.
An adaptive video sub-sampling technique for the conversion between high and low resolution

An adaptive sub-sampling technique is proposed for the conversion of high-resolution video to low-resolution video, which will eventually be converted back to high resolution. This technique can preserve high spatial frequency information by exploiting the temporal correlation of stationary regions without any extra storage or transmission bandwidth. Coding complexity can be reduced by a factor of four if the video is to be eventually displayed in high-resolution, with small degradation in visual quality and peak-signal-to noise ratio. Most of the edge information can be preserved when the low-resolution video is converted back to high-resolution video and significant improvement can be obtained compared with conventional methods.
A novel semi-private watermarking technique

A novel watermarking technique is proposed to embed a semi-watermark in digital images. Before embedding the watermark, a M-dimensional vector is extracted from the original data. Watermarking is achieved by modifying this vector to another particular vector according to the private keys and the watermark. A dual-key system is used to reduce the chance for the removal of watermark. The watermark can be detected without the original image. If the original image is available in the detection of watermark, the proposed technique is almost equivalent to the well known spread spectrum technique.
Digital photo album compression based on Global Motion Compensation and Intra/Inter prediction

With the increasing popularity of digital camera, organizing and managing the large collection of digital photos effectively become popular. Most researchers focus on clustering and image retrieval, but never on photo album compression. Some set redundancy methods for compressing similar image sets cannot handle photo album compression well because they don't account for any camera and object motion information between images. In this paper, we analyzed the characteristics of camera and object motion between similar photos and designed a novel lossy coding scheme for similar image sets. In our proposed coding scheme, we applied Global Motion Compensation (GMC), Local Motion Compensation (LMC) and Intra prediction inspired from video coding technology. Our method provides a compact and reasonable format for people to store and transmit their large number of digital photos. Experiments prove that our algorithm is efficient and effective for digital photo processing.