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Author Hugo Jair Escalante; Victor Ponce; Sergio Escalera; Xavier Baro; Alicia Morales-Reyes; Jose Martinez-Carranza edit   pdf
doi  openurl
  Title Evolving weighting schemes for the Bag of Visual Words Type Journal Article
  Year 2017 Publication Neural Computing and Applications Abbreviated Journal Neural Computing and Applications  
  Volume 28 Issue (down) 5 Pages 925–939  
  Keywords Bag of Visual Words; Bag of features; Genetic programming; Term-weighting schemes; Computer vision  
  Abstract The Bag of Visual Words (BoVW) is an established representation in computer vision. Taking inspiration from text mining, this representation has proved
to be very effective in many domains. However, in most cases, standard term-weighting schemes are adopted (e.g.,term-frequency or TF-IDF). It remains open the question of whether alternative weighting schemes could boost the
performance of methods based on BoVW. More importantly, it is unknown whether it is possible to automatically learn and determine effective weighting schemes from
scratch. This paper brings some light into both of these unknowns. On the one hand, we report an evaluation of the most common weighting schemes used in text mining, but rarely used in computer vision tasks. Besides, we propose an evolutionary algorithm capable of automatically learning weighting schemes for computer vision problems. We report empirical results of an extensive study in several computer vision problems. Results show the usefulness of the proposed method.
 
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  Publisher Place of Publication Editor Springer  
  Language Summary Language Original Title  
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  Notes HUPBA;MV; no menciona Approved no  
  Call Number Admin @ si @ EPE2017 Serial 2743  
Permanent link to this record
 

 
Author Agata Lapedriza; David Masip; Jordi Vitria edit  doi
openurl 
  Title On the Use of External Face Features for Identity Verification Type Journal
  Year 2006 Publication Journal of Multimedia, 1(4): 11–20 Abbreviated Journal  
  Volume 1 Issue (down) 4 Pages 11-20  
  Keywords Face Verification, Computer Vision, Machine Learning  
  Abstract In general automatic face classification applications images are captured in natural environments. In these cases, the performance is affected by variations in facial images related to illumination, pose, occlusion or expressions. Most of the existing face classification systems use only the internal features information, composed by eyes, nose and mouth, since they are more difficult to imitate. Nevertheless, nowadays a lot of applications not related to security are developed, and in these cases the information located at head, chin or ears zones (external features) can be useful to improve the current accuracies. However, the lack of a natural alignment in these areas makes difficult to extract these features applying classic Bottom-Up methods. In this paper, we propose a complete scheme based on a Top-Down reconstruction algorithm to extract external features of face images. To test our system we have performed face verification experiments using public databases, given that identity verification is a general task that has many real life applications. We have considered images uniformly illuminated, images with occlusions and images with high local changes in the illumination, and the obtained results show that the information contributed by the external features can be useful for verification purposes, specially significant when faces are partially occluded.  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ LMV2006b Serial 708  
Permanent link to this record
 

 
Author David Masip; Jordi Vitria edit  openurl
  Title Shared Feature Extraction for Nearest Neighbor Face Recognition Type Journal
  Year 2008 Publication IEEE Transactions on Neural Networks Abbreviated Journal  
  Volume 19 Issue (down) 4 Pages 586–595  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ MaV2008 Serial 944  
Permanent link to this record
 

 
Author Fadi Dornaika; Bogdan Raducanu edit  doi
openurl 
  Title Three-Dimensional Face Pose Detection and Tracking Using Monocular Videos: Tool and Application Type Journal Article
  Year 2009 Publication IEEE Transactions on Systems, Man and Cybernetics part B Abbreviated Journal TSMCB  
  Volume 39 Issue (down) 4 Pages 935–944  
  Keywords  
  Abstract Recently, we have proposed a real-time tracker that simultaneously tracks the 3-D head pose and facial actions in monocular video sequences that can be provided by low quality cameras. This paper has two main contributions. First, we propose an automatic 3-D face pose initialization scheme for the real-time tracker by adopting a 2-D face detector and an eigenface system. Second, we use the proposed methods-the initialization and tracking-for enhancing the human-machine interaction functionality of an AIBO robot. More precisely, we show how the orientation of the robot's camera (or any active vision system) can be controlled through the estimation of the user's head pose. Applications based on head-pose imitation such as telepresence, virtual reality, and video games can directly exploit the proposed techniques. Experiments on real videos confirm the robustness and usefulness of the proposed methods.  
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  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ DoR2009a Serial 1218  
Permanent link to this record
 

 
Author Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu edit   pdf
url  doi
openurl 
  Title New Opportunities for Computer Vision-Based Assistive Technology Systems for the Visually Impaired Type Journal Article
  Year 2014 Publication Computer Abbreviated Journal COMP  
  Volume 47 Issue (down) 4 Pages 52-58  
  Keywords  
  Abstract Computing advances and increased smartphone use gives technology system designers greater flexibility in exploiting computer vision to support visually impaired users. Understanding these users' needs will certainly provide insight for the development of improved usability of computing devices.  
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  Series Volume Series Issue Edition  
  ISSN 0018-9162 ISBN Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ TSR2014a Serial 2317  
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