Comparing objective visual quality impairment detection in 2D and 3D video sequences

The skill level of teleoperator plays a key role in the telerobotic operation. However, plenty of experiments are required to evaluate the skill level in a conventional assessment. In this paper, a novel brain-based method of skill assessment is introduced, and the relationship between the teleoperator's brain states and skill level is first investigated based on a kernel canonical correlation analysis (KCCA) method. The skill of teleoperator (SoT) is defined by a statistic method using the cumulative probability function (CDF). Five indicators are extracted from the electroencephalo-graph (EEG) of the teleoperator to represent the brain states during the telerobotic operation. By using the KCCA algorithm in modeling the relationship between the SoT and the brain states, the correlation has been proved. During the telerobotic operation, the skill level of teleoperator can be well predicted through the brain states. © 2013 IEEE.Link_to_subscribed_fulltex

Make Me Walk, Make Me Talk, Do Whatever You Please: Barbie and Exceptions

Barbie represents an aspiration to an ideal and also a never-ending mutability. Barbie is the perfect woman, and she is also grotesque, plasticized hyperreality, presenting a femininity exaggerated to the point of caricature. Barbie’s marketplace success, combined with (and likely related to) her overlapping and contradictory meanings, also allow her to embody some key exceptions to copyright and trademark law. Though Mattel’s lawsuits were not responsible for the initial recognition of those exceptions, they illuminate key principles and contrasts in American law. Mattel attempted to use both copyright and trademark to control the meaning of Barbie, reflecting a trend towards such overlapping claims. In order to ensure that their combined scope is no greater than the sum of their parts, both trademark and copyright defenses ought to be considered together. The Barbie cases highlight the problem that overlaps between the two regimes can challenge the very idea of IP boundaries, unless robust defenses exist against overclaiming

The Jurisprudence of Transformation: Intellectual Incoherence and Doctrinal Murkiness Twenty Years After Campbell v. Acuff-Rose Music

Examining recent judicial opinions, this Article analyzes and critiques the transformative-use doctrine two decades after the U.S. Supreme Court introduced it into copyright law in Campbell v. Acuff-Rose Music. When the Court established the transformative-use concept, which plays a critical role in fair-use determinations today, its contours were relatively undefined. Drawing on an influential law-review article, the Court described a transformative use as one that adds “new expression, meaning or message.” Unfortunately, the doctrine and its application are increasingly ambiguous, with lower courts developing competing conceptions of transformation. This doctrinal murkiness is particularly disturbing because fair use is a key proxy for First Amendment interests in copyright law. This Article traces the evolution of transformative use, analyzes three key paradigms of transformative use that have gained prominence in the post-Campbell environment, and offers suggestions for a jurisprudence in which transformative use is a less significant component of the fair-use analysis

Visual Comfort Assessment for Stereoscopic Image Retargeting

In recent years, visual comfort assessment (VCA) for 3D/stereoscopic content has aroused extensive attention. However, much less work has been done on the perceptual evaluation of stereoscopic image retargeting. In this paper, we first build a Stereoscopic Image Retargeting Database (SIRD), which contains source images and retargeted images produced by four typical stereoscopic retargeting methods. Then, the subjective experiment is conducted to assess four aspects of visual distortion, i.e. visual comfort, image quality, depth quality and the overall quality. Furthermore, we propose a Visual Comfort Assessment metric for Stereoscopic Image Retargeting (VCA-SIR). Based on the characteristics of stereoscopic retargeted images, the proposed model introduces novel features like disparity range, boundary disparity as well as disparity intensity distribution into the assessment model. Experimental results demonstrate that VCA-SIR can achieve high consistency with subjective perception

3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks

We propose a method for reconstructing 3D shapes from 2D sketches in the form of line drawings. Our method takes as input a single sketch, or multiple sketches, and outputs a dense point cloud representing a 3D reconstruction of the input sketch(es). The point cloud is then converted into a polygon mesh. At the heart of our method lies a deep, encoder-decoder network. The encoder converts the sketch into a compact representation encoding shape information. The decoder converts this representation into depth and normal maps capturing the underlying surface from several output viewpoints. The multi-view maps are then consolidated into a 3D point cloud by solving an optimization problem that fuses depth and normals across all viewpoints. Based on our experiments, compared to other methods, such as volumetric networks, our architecture offers several advantages, including more faithful reconstruction, higher output surface resolution, better preservation of topology and shape structure.Comment: 3DV 2017 (oral