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Artistic style transfer involves the adaption of an input image to reflect the style of a reference image while maintaining its original content. This technique, now a prominent focus due to its prospective use in creative fields like digital art and graphic design, typically applies normalization techniques and attention mechanisms. While these methods yield decent results, they often fall short due to distortion of content image details and non‐artefact styles. In this paper, we introduce a novel approach that synergizes adaptive instance normalization (AdaIN), attention mechanisms, knowledge distillation (KD) and strategically placed internal layers, and new enhancements designed to preserve content details and provide a nuanced control over the style transfer process. We introduce a Detail Enhancement Module to amplify high‐frequency details in the content image, enhancing edge and texture preservation. A Multi‐scale Strategy is implemented to ensure uniform style application across various detail levels, leading to more coherent stylization. The Content Feature Refinement process refines content features, sharpening and emphasizing details to preserve structural and textural integrity. AdaIN's distinctive feature of efficiently collecting style data is exploited in our approach, coupled with attention mechanisms' inherent ability to conserve content information. We supplement this blend with KD for the enhancement of model accuracy and efficiency. Additionally, the introduction of internal layers acts as a conduit to further improve the style transfer process, increasing the transfer level of features and fostering better stylized results. The cornerstone of our technique lies in preserving the content structure amidst complex style transfers. Experimental results affirm the superior performance of our method over existing techniques in both quantitative and qualitative evaluations. [ABSTRACT FROM AUTHOR]

Due to the disadvantages of traditional imaging methods, an imaging method based on object imaging has been proposed in this paper. This imaging method only images objects that are of interest and filters other objects. This paper mainly applies this imaging method to detect the quality of tiles by detection of special shapes. If the printing graphics of the tiles meet our requirements, a quality detection system will display the graphics needing quality detection on a monitor. Otherwise, no graphics are displayed on the monitor if the printing graphics do not meet requirements. The system includes: the use of communication between ARM and DSP under the DM6446 platform, the call to a multiple-algorithm, and design of a specific graphic imaging algorithm. The system removes the artificial testing steps in the process of quality detection, improves the speed and accuracy of quality detection and reduces the labor intensity required from inspectors. The preliminary studies show the feasibility and practicability of this system, and the preliminary experimental results show that an imaging method based on object imaging can be applied to quality detection of tiles and can solve existing problems for quality detection. [ABSTRACT FROM AUTHOR]

This paper presents how to synthesize a texture in a procedural way that preserves the features of the input exemplar. The exemplar is analyzed in both spatial and frequency domains to be decomposed into feature and non-feature parts. Then, the non-feature parts are reproduced as a procedural noise, whereas the features are independently synthesized. They are combined to output a non-repetitive texture that also preserves the exemplar's features. The proposed method allows the user to control the extent of extracted features and also enables a texture to edited quite effectively. [ABSTRACT FROM AUTHOR]

Although a large number of methods for video text detection and recognition have been proposed over the past years, it is hard to find the best state-of-the-art method because of nonavailability of standard datasets, ground truth, and common evaluation measures. Therefore, in this paper, we propose a semiautomatic system for ground truth generation for video text detection and recognition, which includes English and Chinese text of different orientation. The system has a facility to allow the user to manually correct the ground truth if the automatic method produces incorrect results. We propose eleven attributes at the word level, namely: line index, word index, coordinate values of bounding box, area, content, script type, orientation information, type of text (caption/scene), condition of text (distortion/distortion free), start frame, and end frame to evaluate the performance of the method. We also introduce a new dataset that consists of 466 video frames collected from TRECVID 2005 and 2006 databases. The video frames in our dataset contain both horizontal texts (278 frames: 181 with English texts and 97 with Chinese texts) and nonhorizontal texts (188 frames: 140 English and 48 Chinese). Furthermore, the performance of the proposed system is compared with existing text detection methods by calculating measures manually and automatically to show usefulness of our semiautomatic system. The ground truth and the semiautomatic system will be released to the public. [ABSTRACT FROM AUTHOR]

To render 3-D graphics efficiently, rasterization techniques have been developed. Traditional triangle traversal techniques using scan-line-based or edge-equation-based methods may cause potential instability from the division operations. This paper develops an efficient rasterization algorithm—a barycentric-based ladder start tile traversal that is division free. Throughout the process, no extra traversal position and context is produced to reduce the number of pixel tests and improve the efficiency and stability of the graphic rendering. It also presents the architecture of a 300 MHz 3-D graphics rasterizer in a 65 nm 1P9M process with a core size of 0.537 mm \(^{2}\) and internal buffer 3 K. The proposed ladder start tile traversal architecture can perform each tile intersect test in six cycles and tile interior traversal with barycentric tests in 2 pixels per cycle. In addition, the rasterizer throughput can achieve up to 50M triangles per second and 600M pixels per second. [ABSTRACT FROM PUBLISHER]

Abstract: Approximate Nearest Neighbour Field maps are commonly used by computer vision and graphics community to deal with problems like image completion, retargetting, denoising, etc. In this paper, we extend the scope of usage of ANNF maps to medical image analysis, more specifically to optic disk detection in retinal images. In the analysis of retinal images, optic disk detection plays an important role since it simplifies the segmentation of optic disk and other retinal structures. The proposed approach uses FeatureMatch, an ANNF algorithm, to find the correspondence between a chosen optic disk reference image and any given query image. This correspondence provides a distribution of patches in the query image that are closest to patches in the reference image. The likelihood map obtained from the distribution of patches in query image is used for optic disk detection. The proposed approach is evaluated on five publicly available DIARETDB0, DIARETDB1, DRIVE, STARE and MESSIDOR databases, with total of 1540 images. We show, experimentally, that our proposed approach achieves an average detection accuracy of 99% and an average computation time of 0.2s per image. [Copyright &y& Elsevier]

The plenoptic function (POF) provides a powerful conceptual tool for describing a number of problems in image/video processing, vision, and graphics. For example, image-based rendering is shown as sampling and interpolation of the POF. In such applications, it is important to characterize the bandwidth of the POF. We study a simple but representative model of the scene where band-limited signals (e.g., texture images) are “painted” on smooth surfaces (e.g., of objects or walls). We show that, in general, the POF is not band limited unless the surfaces are flat. We then derive simple rules to estimate the essential bandwidth of the POF for this model. Our analysis reveals that, in addition to the maximum and minimum depths and the maximum frequency of painted signals, the bandwidth of the POF also depends on the maximum surface slope. With a unifying formalism based on multidimensional signal processing, we can verify several key results in POF processing, such as induced filtering in space and depth-corrected interpolation, and quantify the necessary sampling rates. [ABSTRACT FROM AUTHOR]

Colour space transformations are frequently used in image processing, graphics and visualisation applications. In many cases, these transformations are complex non-linear functions, which prohibit their use in time-critical applications. A new approach called minimax approximations for colour space transformations (MACT) is presented. The authors demonstrate MACT on three commonly used colour space transformations. Extensive experiments on a large and diverse image set and comparisons with well-known multidimensional look-up table interpolation methods show that MACT achieves an excellent balance among four criteria: ease of implementation, memory usage, accuracy and computational speed. [ABSTRACT FROM AUTHOR]

We present a pipeline to reconstruct complete geometry of architectural buildings from point clouds obtained by sparse range laser scanning. Due to limited accessibility of outdoor environments, complete and sufficient scanning of every face of an architectural building is often impossible. Our pipeline deals with architectures that are made of planar faces and faithfully constructs a polyhedron of low complexity based on the incomplete scans. The pipeline first recognizes planar regions based on point clouds, then proceeds to compute plane intersections and corners (in this paper, we use the informal terms corner or vertex corner to stand for a polyhedron vertex. See the Overview section for notation declarations), and finally produces a complete polyhedron. Within the pipeline, several algorithms based on the polyhedron geometry assumption are designed to perform data clustering, boundary detection, and face extraction. Our system offers a convenient user interface but minimizes the necessity of user intervention. We demonstrate the capability and advantage of our system by modeling real-life buildings. [ABSTRACT FROM AUTHOR]

Radial basis functions are a popular basis for interpolating scattered data during the image reconstruction process in graphic analysis. In this context, the solution of a linear system of equations represents the most time-consuming operation. In this paper an efficient preconditioning technique is proposed to solve these linear systems of equations. This algorithm consists of an iterative method which enforces at each iteration a projection of the residual onto a suitable subspace called coarse space. This constraint is ensured by solving an auxiliary problem at each iteration without regularisation. As increasing the number of the coarse space basis functions increases the computational cost of the algorithm, correct selection of coarse space basis is addressed in the paper. Numerical results illustrate the convergence properties of the proposed method with wavelet-like basis functions and regular distributed radial basis functions for image reconstruction. [Copyright &y& Elsevier]

In electrophotographic printing, a periodic clustered-dot halftone pattern is preferred for a smooth and stable result. In addition, the screen frequency should be high enough to minimize the visibility of the halftone textures and to ensure good detail rendition. However, at these frequencies, the halftone cell may contain too few pixels to provide a sufficient number of dis- tinct gray levels. This will result in contouring and posterization. The traditional solution is to grow the clusters asynchronously within a repeating block of clusters known as a supercell. The growth of each individual cluster is governed by a microscreen. The order in which the clusters grow within the supercell is determined by a macroscreen. Typically, the macroscreen is a recursive pattern due to Bayer. In highlights and shadows, this ordering results in visible artifacts. Replacing the Bayer screen by a stochastic macroscreen eliminates these artifacts, but results in new artifacts. In this paper, we propose a new composite screen architecture that employs multiple microscreens and multiple macroscreens in the highlights and shadows. These screens are jointly designed by using the direct binary search (DBS) algorithm. [ABSTRACT FROM AUTHOR]

Combinatorial graph cut algorithms have been successfully applied to a wide range of problems in vision and graphics. This paper focusses on possibly the simplest application of graph-cuts: segmentation of objects in image data. Despite its simplicity, this application epitomizes the best features of combinatorial graph cuts methods in vision: global optima, practical efficiency, numerical robustness, ability to fuse a wide range of visual cues and constraints, unrestricted topological properties of segments, and applicability to N-D problems. Graph cuts based approaches to object extraction have also been shown to have interesting connections with earlier segmentation methods such as snakes, geodesic active contours, and level-sets. The segmentation energies optimized by graph cuts combine boundary regularization with region-based properties in the same fashion as Mumford-Shah style functionals. We present motivation and detailed technical description of the basic combinatorial optimization framework for image segmentation via s/ t graph cuts. After the general concept of using binary graph cut algorithms for object segmentation was first proposed and tested in Boykov and Jolly (2001), this idea was widely studied in computer vision and graphics communities. We provide links to a large number of known extensions based on iterative parameter re-estimation and learning, multi-scale or hierarchical approaches, narrow bands, and other techniques for demanding photo, video, and medical applications. [ABSTRACT FROM AUTHOR]

This article presents an automatic system that takes in grayscale scanned images, which could be mixed text/graphic documents, and performs thresholding and skew detection on the document images. The system consists of two major components; multistage thresholding and skew detection. The proposed skew detection algorithm has no restriction on detectable angle range and does not rely on large blocks of text. It works well on textual document images, graphical images and mixed text and graphic images. The performance of the systems was evaluated using over 60 images that consist of real life documents like envelopes and artificial mixed text/graphic icons. The superior performance of thresholding is clear compared to other techniques from the evaluation. The skew detection algorithm is robust when compared with other methods when very few text lines are present in the document image. [ABSTRACT FROM AUTHOR]

This paper describes a computer vision system based on active IR illumination for real-time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a hierarchical classification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about 5° horizontally and 8° vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display. [ABSTRACT FROM AUTHOR]

There is a potential conflict in the design of interactive narratives. The exercise of interaction in digital environments, including games, may interfere with the experience of story. The article uses the interactive CD-ROM CEREMONY OF INNOCENCE as a case study in the resolution of this potential conflict. It frames the design of this interactive narrative as the reconciliation of two independent design domains: the design of narrative and interactive design. Narrative design seeks a state of immersive surrender to the work. In contrast, interaction privileges choice and its consequences according to the logic of the interactive world. CEREMONY OF INNOCENCE uses two tactics to overcome this disjuncture. The first is the broad infusion of narrative sensibilities in the detailed design of the work's subsidiary craft (sound, graphics, moving images, and text). The second tactic is to suborn certain design specifics of the interactive interface to the goals of narrative design. [ABSTRACT FROM AUTHOR]