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Author Thierry Brouard; Jordi Gonzalez; Caifeng Shan; Massimo Piccardi; Larry S. Davis edit   pdf
doi  openurl
  Title Special issue on background modeling for foreground detection in real-world dynamic scenes Type Journal Article
  Year 2014 Publication Machine Vision and Applications Abbreviated Journal MVAP  
  Volume 25 Issue 5 Pages 1101-1103  
  Keywords  
  Abstract Although background modeling and foreground detection are not mandatory steps for computer vision applications, they may prove useful as they separate the primal objects usually called “foreground” from the remaining part of the scene called “background”, and permits different algorithmic treatment in the video processing field such as video surveillance, optical motion capture, multimedia applications, teleconferencing and human–computer interfaces. Conventional background modeling methods exploit the temporal variation of each pixel to model the background, and the foreground detection is made using change detection. The last decade witnessed very significant publications on background modeling but recently new applications in which background is not static, such as recordings taken from mobile devices or Internet videos, need new developments to detect robustly moving objects in challenging environments. Thus, effective methods for robustness to deal both with dynamic backgrounds, i  
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  Publisher Springer Berlin Heidelberg Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN 0932-8092 ISBN Medium  
  Area Expedition Conference  
  Notes ISE; 600.078 Approved no  
  Call Number (down) BGS2014a Serial 2411  
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Author Maria Vanrell; Jordi Vitria; Xavier Roca edit  openurl
  Title A multidimensional scaling approach to explore the behavior of a texture perception algorithm. Type Journal Article
  Year 1997 Publication Machine Vision and Applications Abbreviated Journal  
  Volume 9 Issue Pages 262–271  
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  Notes OR;ISE;CIC;MV Approved no  
  Call Number (down) BCNPCL @ bcnpcl @ VVR1997 Serial 35  
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Author A. Toet; M. Henselmans; M.P. Lucassen; Theo Gevers edit  doi
openurl 
  Title Emotional effects of dynamic textures Type Journal
  Year 2011 Publication i-Perception Abbreviated Journal iPER  
  Volume 2 Issue 9 Pages 969 – 991  
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  Abstract This study explores the effects of various spatiotemporal dynamic texture characteristics on human emotions. The emotional experience of auditory (eg, music) and haptic repetitive patterns has been studied extensively. In contrast, the emotional experience of visual dynamic textures is still largely unknown, despite their natural ubiquity and increasing use in digital media. Participants watched a set of dynamic textures, representing either water or various different media, and self-reported their emotional experience. Motion complexity was found to have mildly relaxing and nondominant effects. In contrast, motion change complexity was found to be arousing and dominant. The speed of dynamics had arousing, dominant, and unpleasant effects. The amplitude of dynamics was also regarded as unpleasant. The regularity of the dynamics over the textures’ area was found to be uninteresting, nondominant, mildly relaxing, and mildly pleasant. The spatial scale of the dynamics had an unpleasant, arousing, and dominant effect, which was larger for textures with diverse content than for water textures. For water textures, the effects of spatial contrast were arousing, dominant, interesting, and mildly unpleasant. None of these effects were observed for textures of diverse content. The current findings are relevant for the design and synthesis of affective multimedia content and for affective scene indexing and retrieval.  
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  Series Volume Series Issue Edition  
  ISSN 2041-6695 ISBN Medium  
  Area Expedition Conference  
  Notes ALTRES;ISE Approved no  
  Call Number (down) Admin @ si @THL2011 Serial 1843  
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Author Zeynep Yucel; Albert Ali Salah; Çetin Meriçli; Tekin Meriçli; Roberto Valenti; Theo Gevers edit  doi
openurl 
  Title Joint Attention by Gaze Interpolation and Saliency Type Journal
  Year 2013 Publication IEEE Transactions on cybernetics Abbreviated Journal T-CIBER  
  Volume 43 Issue 3 Pages 829-842  
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  Abstract Joint attention, which is the ability of coordination of a common point of reference with the communicating party, emerges as a key factor in various interaction scenarios. This paper presents an image-based method for establishing joint attention between an experimenter and a robot. The precise analysis of the experimenter's eye region requires stability and high-resolution image acquisition, which is not always available. We investigate regression-based interpolation of the gaze direction from the head pose of the experimenter, which is easier to track. Gaussian process regression and neural networks are contrasted to interpolate the gaze direction. Then, we combine gaze interpolation with image-based saliency to improve the target point estimates and test three different saliency schemes. We demonstrate the proposed method on a human-robot interaction scenario. Cross-subject evaluations, as well as experiments under adverse conditions (such as dimmed or artificial illumination or motion blur), show that our method generalizes well and achieves rapid gaze estimation for establishing joint attention.  
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  ISSN 2168-2267 ISBN Medium  
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  Notes ALTRES;ISE Approved no  
  Call Number (down) Admin @ si @ YSM2013 Serial 2363  
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Author Yecong Wan; Yuanshuo Cheng; Miingwen Shao; Jordi Gonzalez edit  doi
openurl 
  Title Image rain removal and illumination enhancement done in one go Type Journal Article
  Year 2022 Publication Knowledge-Based Systems Abbreviated Journal KBS  
  Volume 252 Issue Pages 109244  
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  Abstract Rain removal plays an important role in the restoration of degraded images. Recently, CNN-based methods have achieved remarkable success. However, these approaches neglect that the appearance of real-world rain is often accompanied by low light conditions, which will further degrade the image quality, thereby hindering the restoration mission. Therefore, it is very indispensable to jointly remove the rain and enhance illumination for real-world rain image restoration. To this end, we proposed a novel spatially-adaptive network, dubbed SANet, which can remove the rain and enhance illumination in one go with the guidance of degradation mask. Meanwhile, to fully utilize negative samples, a contrastive loss is proposed to preserve more natural textures and consistent illumination. In addition, we present a new synthetic dataset, named DarkRain, to boost the development of rain image restoration algorithms in practical scenarios. DarkRain not only contains different degrees of rain, but also considers different lighting conditions, and more realistically simulates real-world rainfall scenarios. SANet is extensively evaluated on the proposed dataset and attains new state-of-the-art performance against other combining methods. Moreover, after a simple transformation, our SANet surpasses existing the state-of-the-art algorithms in both rain removal and low-light image enhancement.  
  Address Sept 2022  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
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  Notes ISE; 600.157; 600.168 Approved no  
  Call Number (down) Admin @ si @ WCS2022 Serial 3744  
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