Most previous works on saliency detection are dedicated to 2D images. Recently it has been shown that 3D visual information supplies a powerful cue for analysis. In this paper, we propose novel method depth images based anisotropic center-surround difference. Instead of depending absolute depth, measure the point by how much outstands from surroundings, which takes global structure into consideration. Besides, two common priors and location used refinement. The proposed within complexity...

VR/AR is rapidly progressing towards enterprise and end customers with the promise of bringing immersive experience to numerous applications. Soon it will target smartphones from cloud 360° video delivery need unprecedented requirements for ultra-low latency ultra-high throughput mobile networks. Latest developments in NFV Mobile Edge Computing reveal already potential enable VR streaming cellular networks pave way 5G next stages technology.

This paper proposes G-VIDO, a vehicle dynamics, and intermittent Global Navigation Satellite System (GNSS)-aided visual-inertial state estimator, to address the estimation problem of autonomous localization (i.e., position orientation in global coordinate system) under various GNSS states. A dynamics pre-integration theory is proposed on basis two-degree-of-freedom (DOF) model, constraints are built optimization back-end, considering unobservable monocular system degenerate motions. The...

Online VR streaming faces great challenges such as the high throughput and real time interaction requirement. In this paper, we propose a novel ultra wide view based method to stream quality on Internet at low bandwidth little computation cost. First, only transmit region where user is looking instead of full 360° save bandwidth. To achieve goal, split source into small grid videos in advance. The are able reconstruct any flexibly end. Second, according fact that users generally interact...

Recent years, the stereo image has become an emerging media in field of 3D technology, which leads to urgent demand retrieval. In this paper, we attempt introduce a framework for object-based retrieval (OBSIR), retrieves images containing similar objects one captured query by user. The proposed approach consists both online and offline procedures. procedure, propose salient object segmentation method making use color depth extract from each image. extracted are then represented multiple...

Salient object detection attracts much attention for its effectiveness in numerous applications. However, how to effectively produce a high quality binary mask from saliency map, named cuts, is still an open problem. In this paper, we propose novel cuts approach using unsupervised seeds generation and GrabCut algorithm. With the input of segmentation adaptive triple thresholding, feed Finally, generated by iteratively optimization. The experimental results show that proposed competent task...

Let $\Gamma$ be a bipartite graph, and let $\mathrm{Aut}\Gamma$ the full automorphism group of graph $\Gamma$. A subgroup $G\leqslant \mathrm{Aut}\Gamma$ is said to bi-regular on if $G$ preserves bipartition acts regularly both parts $\Gamma$, while called bi-Cayley in this case. $X\leqslant \mathrm{Aut} \Gamma$ bi-quasiprimitive bipartition-preserving $X$ quasiprimitive each part $\Gamma$.
 In paper, characterization given for connected graphs nonabelian simple groups which have prime...

Consistent object extraction plays an essential role for stereo image editing with the population of stereoscopic 3D media. Most previous methods perform segmentation on entire images both views using dense correspondence constraints. We find that such kind computation is highly redundant since two are near-duplicate. Besides, consistency may be violated due to imperfectness current matching algorithms. In this paper, we propose a contour based method which searches consistent contours...

Current saliency detection methods mainly work on exploring the potential of low-level and high-level visual features, such as color, texture face, but treat location information a weak assistance or completely ignore it. In this paper, we reveal importance in detection. We analyze largest public image dataset for THUS10000, relationship between content distribution. To further validate effect information, propose two based approaches, Gaussian distribution propagation, which make use no...

Reducing network latency has always been a challenging problem due to the diversity of its potential causes. Though there have many successful solutions, they are limited certain applications or suffering from high resource consumption. In this paper, we propose hybrid architecture which combines existing methods meet low requirements future Internet services. We first make comprehensive survey solutions and employ classical queueing model analyze strengths weaknesses them. Then present our...

Smart devices have pervaded every aspect of humans' daily lives. Though single device UX products are relatively successful, the experience cross-device interaction is still far from satisfactory and can be a source frustration. Inconsistent UI styles, unclear coordination, varying fidelity, pairwise interactions, lack understanding intent, limited data sharing security, other problems typically degrade in multi-device ecosystem. Redesigning UX, tailored to ecosystems enhance user...

The goal of low-light image enhancement is to restore the color and details great significance for high-level visual tasks in autonomous driving. However, it difficult lost dark area by relying only on RGB domain. In this paper we introduce frequency as a new clue into network propose novel DCT-driven transformer (DEFormer). First, learnable branch (LFB) contains DCT processing curvature-based (CFE). CFE calculates curvature each channel represent detail richness different bands, then...

Data mining techniques have garnered significant attention within the realm of education. However, procurement ample student data poses a formidable challenge. In response to this challenge, we present dataset characterized by its size and distinctive attributes. This encompasses various task-related topics interconnected through learning pathway, thereby enabling researchers delve into from novel perspectives. Moreover, it extensive longitudinal behavioral data, rarity that adds substantial...

Intelligent Tutoring Systems (ITS) are increasingly popular for online learning. These systems use adaptive algorithms to recommend relevant content based on students' profiles. However, instructors need periodically assess performance ensure learning outcomes and adjust strategies accordingly. Our objective is predict progress in advance, enabling teachers make quicker decisions facilitating the iterative process of algorithms. For this study, we collected a dataset from ALIN, an platform,...

In this paper, we propose an effective local stereo matching method based on extended triangular interpolation. The whole image is covered with a mesh by performing triangulation set of initial support points. Since the disparity interpolation in some areas ineffective, especially triangle which appears across boundaries objects or formed outliers, formulate new model Bayesian rule to address challenge. model, introduce concept triangle's reliability, and utilize planes determined...