An efficient video watermarking based security model

Microsystem Technologies - Watermarking is defined as about hiding any valuable information set in the particular digital media by itself through modifying the particular graphic contents. In our...     

结合HVS和相似性度量的图像质量评价测度

图像质量评价是图像处理领域内一项很有意义的研究课题。传统的评价方法(如PSNR和MSE)只是在像素域统计参考图像和失真图像的误差,因而不能有效反映图像的视觉感知质量。针对上述问题,在充分考虑人眼视觉感知特性的基础上,提出一种新颖的图像质量评价算法,通过模拟人类视觉系统,并结合相似性度量方法获得有效的图像质量评价测度。实验结果显示,采用本文方法获得的图像质量评价结果与主观感知具有较好的一致性,能准确地反映人眼对图像质量的视觉感知。     

A real-time 3D video analyzer for enhanced 3D audio–visual systems

Multimedia Systems - With the recent advent of three-dimensional (3D) sound home theater systems (HTS), more and more TV viewers are experiencing rich, immersive auditory presence at home. In this...     

基于深度的3D视频质量评价

针对3D视频质量评价,基于人眼视觉系统HVS提出了一种新的加权SSIM评测方法.利用MVD深度视图空间和时间上的特性,提取主观权值映射,基于SSIM利用权值映射使得到了基于深度的SSIM加权算法DSSIM.实验结果表明,DSSIM比PSNR更趋近于HVS,比SSIM更充分地考虑了3D结构信息,得到更准确的3D视频质量评价.     

SVD-based quality metric for image and video using machine learning

We study the use of machine learning for visual quality evaluation with comprehensive singular value decomposition (SVD)-based visual features. In this paper, the two-stage process and the relevant work in the existing visual quality metrics are first introduced followed by an in-depth analysis of SVD for visual quality assessment. Singular values and vectors form the selected features for visual quality assessment. Machine learning is then used for the feature pooling process and demonstrated to be effective. This is to address the limitations of the existing pooling techniques, like simple summation, averaging, Minkowski summation, etc., which tend to be ad hoc. We advocate machine learning for feature pooling because it is more systematic and data driven. The experiments show that the proposed method outperforms the eight existing relevant schemes. Extensive analysis and cross validation are performed with ten publicly available databases (eight for images with a total of 4042 test images and two for video with a total of 228 videos). We use all publicly accessible software and databases in this study, as well as making our own software public, to facilitate comparison in future research.     

A learning-based visual saliency prediction model for stereoscopic 3D video (LBVS-3D)

Saliency prediction models provide a probabilistic map of relative likelihood of an image or video region to attract the attention of the human visual system. Over the past decade, many computational saliency prediction models have been proposed for 2D images and videos. Considering that the human visual system has evolved in a natural 3D environment, it is only natural to want to design visual attention models for 3D content. Existing monocular saliency models are not able to accurately predict the attentive regions when applied to 3D image/video content, as they do not incorporate depth information. This paper explores stereoscopic video saliency prediction by exploiting both low-level attributes such as brightness, color, texture, orientation, motion, and depth, as well as high-level cues such as face, person, vehicle, animal, text, and horizon. Our model starts with a rough segmentation and quantifies several intuitive observations such as the effects of visual discomfort level, depth abruptness, motion acceleration, elements of surprise, size and compactness of the salient regions, and emphasizing only a few salient objects in a scene. A new fovea-based model of spatial distance between the image regions is adopted for considering local and global feature calculations. To efficiently fuse the conspicuity maps generated by our method to one single saliency map that is highly correlated with the eye-fixation data, a random forest based algorithm is utilized. The performance of the proposed saliency model is evaluated against the results of an eye-tracking experiment, which involved 24 subjects and an in-house database of 61 captured stereoscopic videos. Our stereo video database as well as the eye-tracking data are publicly available along with this paper. Experiment results show that the proposed saliency prediction method achieves competitive performance compared to the state-of-the-art approaches.

     

An efficient 3D mesh generator based on geometry decomposition

A new, efficient 3D mesh generation algorithm, hexahedral mesh for urban terrains (HeMUT), is presented. HeMUT is developed under .NET and builds unstructured/structured hexahedral meshes. The algorithm focuses on urban terrains and on the mesh generation for the simulation of toxic gases dispersion (finite element). HeMUT is fully automated, multi-threading and takes advantage of terrain. In addition, it distributes the nodes on the domain by employing a method based on process design considerations. These features decrease the computational effort and at the same time differentiate this algorithm from all other similar ones. In comparison with a commercial software HeMUT performed well.     

An effective 3D target recognition model imitating robust methods of the human visual system

This paper presents a model of 3D object recognition motivated from the robust properties of human vision system (HVS). The HVS shows the best efficiency and robustness for an object identification task. The robust properties of the HVS are visual attention, contrast mechanism, feature binding, multi-resolution, size tuning, and part-based representation. In addition, bottom-up and top-down information are combined cooperatively. Based on these facts, a plausible computational model integrating these facts under the Monte Carlo optimization technique was proposed. In this scheme, object recognition is regarded as a parameter optimization problem. The bottom-up process is used to initialize parameters in a discriminative way; the top-down process is used to optimize them in a generative way. Experimental results show that the proposed recognition model is feasible for 3D object identification and pose estimation in visible and infrared band images.     

一种视频质量智能检测系统的研究

目前的视频监控系统对于摄像头的维护还是主要依靠人工巡查的方式检测摄像头画面质量,工作量大,工作效率低。本文提出了一种视频质量智能检测系统,对视频图像出现的雪花、滚屏、模糊、偏色、画面冻结、增益失衡、云台失控、视频信号丢失等等多种摄像头故障、视频信号干扰、视频质量下降进行准确分析、判断和报警。     

An efficient similarity metric for omnidirectional vision sensors

This paper presents an efficient metric for the computation of the similarity among omnidirectional images (image matching). The representation of image appearance is based on feature vectors that include both the chromatic attributes of color sets and their mutual spatial relationships. The proposed metric fits well to robotic navigation using omnidirectional vision sensors, because it has very important properties: it is reflexive, compositional and invariant with respect to image scaling and rotation. The robustness of the metric was repeatedly tested using omnidirectional images for a robot localization task in a real indoor environment.     

An automatic 2D to 3D video conversion approach based on RGB-D images

3D movies/videos have become increasingly popular in the market; however, they are usually produced by professionals. This paper presents a new technique for the automatic conversion of 2D to 3D video based on RGB-D sensors, which can be easily conducted by ordinary users. To generate a 3D image, one approach is to combine the original 2D color image and its corresponding depth map together to perform depth image-based rendering (DIBR). An RGB-D sensor is one of the inexpensive ways to capture an image and its corresponding depth map. The quality of the depth map and the DIBR algorithm are crucial to this process. Our approach is twofold. First, the depth maps captured directly by RGB-D sensors are generally of poor quality because there are many regions missing depth information, especially near the edges of objects. This paper proposes a new RGB-D sensor based depth map inpainting method that divides the regions with missing depths into interior holes and border holes. Different schemes are used to inpaint the different types of holes. Second, an improved hole filling approach for DIBR is proposed to synthesize the 3D images by using the corresponding color images and the inpainted depth maps. Extensive experiments were conducted on different evaluation datasets. The results show the effectiveness of our method.

     

DCT-based objective quality assessment metric of 2D/3D image

With the increasing growth of multimedia applications over the networking in recent years, users have put forward much higher requirements for multimedia quality of experience (QoE) than before. One of the representative requirements is the image quality. Therefore, the image quality assessment ranging from two-dimension (2D) image to three-dimension (3D) image has been getting much attention. In this paper, an efficient objective image quality assessment metric in block-based discrete cosine transform (DCT) coding is proposed. The metric incorporates properties of human visual system (HVS) to improve its validity and reliability in evaluating the quality of stereoscopic image. This is fulfilled by calculating the local pixel-based distortions in frequency domain, combining the simplified models of local visibility properties embodied in frequency domain, which consist of region of interest (ROI) mechanism (visual sensitivity), contrast sensitivity function (CSF) and contrast masking effect. The performance of the proposed metric is compared with other currently state-of-the-art objective image quality assessment metrics. The experimental results have demonstrated that the proposed metric is highly consistent with the subjective test scores. Moreover, the performance of the metric is also confirmed with the popular IRCCyN/IVC database. Therefore, the proposed metric is promising in term of the practical efficiency and reliability for real-life multimedia applications.     

Low-bandwidth 3D visual telepresence system

We present a methodology to develop a low-cost, low-bandwidth visual telepresence system using commodity depth sensors. To obtain a precise representation of the participants, we fuse together multiple views extracted using a deep background subtraction method. We build a proof-of-concept display composed of a video projector and a quadrangular pyramid made of acrylic, to demonstrate the visualization of a remote person without the need for head-mounted displays. Our system represents an attempt to democratize high-fidelity 3D telepresence using off-the-shelf components.

     

微机版实时三维视景系统的帧率控制

介绍了在微机版塔台模拟机系统中,如何有效地控制其实时三维视景部分的帧率,以达到一个稳定性更高交互性更强的视景仿真环境。采用多台微机协作模拟机场塔台的窗外场景,创造性地提出了视景服务器和从视景位的概念,由从视景位实现单个通道的渲染,而由视景服务器完成各从视景位之间的同步和帧率控制。视景服务器开辟一个缓冲区预存一定数目的帧包来减少网络的延迟,同时根据缓冲区中帧包的平均数目动态调整系统与视景服务器之间的时钟计时精度误差,来缓解由于网络原因造成的帧率失调。视景服务器通过一定的算法维持固定的帧发送率,使从视景位维持固定的帧率来实现彼此之间的同步。     

基于视觉感知的网络视频质量评价方法研究

网络视频在传输过程中,因编码失真或丢包失真,给用户带来明显的视觉影响。传统的均方误差和峰值信噪比的质量评价方法未考虑到人眼视觉特性。文章首先描述了人类视觉系统的基本特性,然后介绍了主客观质量评价方法的优缺点及适用环境,最后采用LIVE视频数据库,对比几种质量评价方法,结果表明,融入视觉感知的评价方法更接近于人眼效果。