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Segmentation of moving objects in a scene is difficult for non-stationary cameras, and especially challenging in the presence of fast and unstable egomotion, e.g., as encountered with car-mounted cameras or wearable devices. Based on an analysis of motion vanishing points of the scene and estimated depth, a geometric model that relates extracted 2D motion to a 3D motion field relative to the camera...
We propose a nuclear-norm regularized two-dimensional neighborhood preserving projection (2DNPP) for extracting representative 2D image features. Note that 2DNPP extracts neighborhood preserving features through minimizing the reconstruction error, but the Frobenius norm based metric is sensitive to noise and outliers. To make the distance metric more reliable and model the neighborhood reconstruction...
Regular omnidirectional video encoding technics use map projection to flatten a scene from a spherical shape into one or several 2D shapes. Common projection methods including equirectangular and cubic projection have varying levels of interpolation that create a large number of non-information-carrying pixels that lead to wasted bitrate. In this paper, we propose a tile based omnidirectional video...
This paper proposes a framework for tracking multiple fluorescent objects in 2D + time video-microscopy. We present a novel batch-processing track-before-detect multiple object tracking approach based on a spatio-temporal marked point process model of ellipses. Our approach takes into account events such as births, deaths, splits and merges of objects which are motivated by the biological and physical...
In this paper, we propose a novel scheme for automatic recognition of facial expressions captured from both fronto-parallel and non-fronto-parallel cameras i.e., multi-view facial expressions (MVFE). The proposed scheme introduce a Local Saliency-inspired Binary Pattern (LSiBP) feature to recognize MVFE. First view-specific approximated saliency likelihood map (ASLM) is derived during training of...
A discriminative dictionary learning algorithm is proposed to find sparse signal representations using relative attributes as the available semantic information. In contrast, existing (discriminative) dictionary learning (DDL) approaches mostly utilize binary label information to enhance the discriminative property of the signal reconstruction residual, the sparse coding vectors or both. Compared...
Incoherent holography has recently attracted significant research interest due to its flexibility for a wide variety of light sources. In this paper, we use compressive sensing to reconstruct a three-dimensional volumetric object from its two-dimensional Fresnel incoherent correlation hologram. We show how compressed sensing enables reconstruction without out-of-focus artifacts, when compared to conventional...
We propose in this paper a novel perceptual viewpoint-independent metric for the quality assessment of 3D meshes. This full-reference objective metric relies on the method proposed by Wang et al. [1] that compares the structural informations between an original signal and a distorted one. In order to extract the structural informations of a 3D mesh, we use a multi-scale visual saliency map on which...
Depth-Image-Based-Rendering (DIBR) is fundamental in free-viewpoint 3D video, which has been widely used to generate synthesized views from multi-view images. The majority of DIBR algorithms cause disoccluded regions, which are the areas invisible in original views but emerge in synthesized views. The quality of synthesized images is mainly contaminated by distortions in these disoccluded regions...
This paper proposes a new temporal consistency measure for quality assessment of synthesized video. Disocclusion regions appear hole regions of the synthesized video at virtual viewpoints. Filling hole regions could be problematic when the synthesized video is perceived through multi-view displays. In particular, the temporal inconsistency caused by hole filling process in view synthesis could affect...
This paper presents a method to stabilize shaky stereoscopic videos captured by hand-held devices. Directly applying traditional monocular video stabilization techniques to two views independently is problematic as it often brings undesirable vertical disparities and produces inaccurate horizontal disparities, which violate original stereoscopic disparity constraints, leading to erroneous depth perception...
In this paper, we propose a novel, full-body, real-time 3D reconstruction framework that makes use of pre-scanned body parts (more precisely pre-scanned 3D heads) so as to provide a more detailed 3D reconstruction mainly in the semantically important head area. Our framework deals with 3 major challenges: a) multiple depth sensors collaboration, b) pre-scanned head positioning and c) reconstruction...
We propose a new compression method devoted to large structured hexahedral meshes having discontinuities. It is dedicated to applications such as visualization or physical simulations whose management by any workstation or mobile device with limited memory and bandwidth is critical. Our method relies on a multiresolution analysis that generates a hierarchy of meshes at increasing resolutions. Our...
We propose optimal rate-allocation, using viewer attention information among viewpoints, for depth map cameras within a free-viewpoint television broadcast system. An attention-weighted rate-allocation framework enables bit-rate, or quality, to be distributed across the multiple cameras in accordance with viewer interest, minimizing total observed distortions perceived among all viewers. Prior work...
This paper investigates the properties of the common self-polar triangle of separate coplanar circles and applies them to camera calibration. We find that any two separate circles have a unique common self-polar triangle. In particular, we show that one vertex of the common self-polar triangle lies on the line at infinity. Given three separate circles, the line at infinity can be recovered using the...
We develop an unsupervised graph clustering and image segmentation algorithm based on non-negative matrix factorization. We consider arbitrarily represented visual signals (in 2D or 3D) and use a graph embedding approach for image or point cloud segmentation. We extend a Projective Non-negative Matrix Factorization variant to include local spatial relationships over the image graph. By using properly...
Objects in fine-grained categories always share a high degree of shape similarity, making both “localizing discriminative parts” and “learning appearance descriptors” extremely difficult. We propose a framework to leverage 2D+3D cues to handle above two challenges. Towards the goal of image alignment to localize discriminative parts, traditional methods rely on either manual part annotation or image...
In this work we propose a depth estimation method for light field images. Light field images can be considered as a collection of 2D images taken from different viewpoints arranged in a regular grid. This means that disparity is the same for any pair of consecutive views, in both vertical and horizontal directions. We exploit this fact by computing disparity maps between specific pairs of views. This...
Light field cameras generate low-resolution images due to the tradeoff between spatial and angular resolution. Traditional light field super-resolution (LFSR) methods depend on prior knowledge of depth information. This paper presents a projection-based LFSR solution without prior information based on redefinition of the mapping function between disparity and shearing shift. Moreover, simplified variational...
How to avoid the invading of the attack in the biometric system, such as 2D printed photos, gradually becomes an important research hotspot. In this paper, we present a novel descriptor in light field to tackle the issue. Based on the angular and spatial information in light field, the proposed light field histogram of gradient (LFHoG) descriptor is derived from three directions, including vertical,...
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