Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Browse by topic Browse by titles Authors Reviewers Browse by issue Browse Help
Search
  Browse All Reviews > Computing Methodologies (I) > Image Processing And Computer Vision (I.4) > Scene Analysis (I.4.8) > Object Recognition (I.4.8...)  
 
Options:
 
  1-10 of 40 Reviews about "Object Recognition (I.4.8...)": Date Reviewed
   Dense 3D-convolutional neural network for person re-identification in videos
Liu J., Zha Z., Chen X., Wang Z., Zhang Y. ACM Transactions on Multimedia Computing, Communications, and Applications 15(1s): 1-19, 2019.  Type: Article

It is well known that the current types of neural networks perform quite well in identifying faces in (still) images. But what about re-identifying moving pedestrians in non-overlapping video sequences taken from different cameras?...

Apr 19 2019
  Facial expression analysis and expression-invariant face recognition by manifold-based synthesis
Peng Y., Yin H. Machine Vision and Applications 29(2): 263-284, 2018.  Type: Article

Although an old topic of exploration, facial expression has become an important field of research. Marketing and medical research frequently use emotion analysis to identify customer needs and emotions....

Aug 23 2018
  Instance-based object recognition in 3D point clouds using discriminative shape primitives
Zhang J., Sun J. Machine Vision and Applications 29(2): 285-297, 2018.  Type: Article

The subject matter of this paper is 3D object recognition, particularly the detection of “objects of interest from cluttered 3D scenes” along with 3D poses of the objects. In fact, the authors study instance-based 3...

Jun 5 2018
  Salient object detection: a discriminative regional feature integration approach
Wang J., Jiang H., Yuan Z., Cheng M., Hu X., Zheng N. International Journal of Computer Vision 123(2): 251-268, 2017.  Type: Article

Visual saliency refers to the distinct subjective perceptual quality that allows a particular object in a scene to stand out from the background and from other neighboring objects to grab our attention. It is a fundamental problem in s...

Nov 1 2017
  Presentation attack detection methods for face recognition systems: a comprehensive survey
Ramachandra R., Busch C. ACM Computing Surveys 50(1): 1-37, 2017.  Type: Article

This paper deals in general with biometric technology and specifically with facial recognition. In this offering, the authors present an exhaustive review of all pioneering efforts on facial presentation attack detection (PAD) algorith...

May 30 2017
  A dimensionality reduction method based on structured sparse representation for face recognition
Gu G., Hou Z., Chen C., Zhao Y. Artificial Intelligence Review 46(4): 431-443, 2016.  Type: Article

Face recognition (FR) is considered to be a typical machine learning problem. Among all FR algorithms, popular models include classical linear models such as eigen face, nonlinear models such as manifold learning, and sparse representa...

Jan 23 2017
  Reading the legends of Roman Republican coins
Kavelar A., Zambanini S., Kampel M. Journal on Computing and Cultural Heritage 7(1): 1-20, 2014.  Type: Article

If you Google “Republican Roman coins” you will be faced with thousands of fascinating images. There are three identifying features on most of them. Most show a head or object. Most have a mark identifying the mint....

Sep 14 2015
  Face detection and recognition on mobile devices
Liu H., Morgan Kaufmann Publishers Inc., Waltham, MA, 2015. 44 pp.  Type: Book (978-0-124170-45-2)

Mobile devices have unique opportunities to interact with their environment; one key capability in this regard is the detection and recognition of human faces. Uses ranging from security to entertainment can be supported by determining...

Aug 4 2015
  Classification and boosting with multiple collaborative representations
Chi Y., Porikli F. IEEE Transactions on Pattern Analysis and Machine Intelligence 36(8): 1519-1531, 2014.  Type: Article

The multiclass classification problem is decomposed into two parts in this paper. The first step is to find a collaborative representation. The idea here is that a collaborative representation sees an example as a mixture of samples fr...

Apr 7 2015
  Handbook of iris recognition
Burge M., Bowyer K., Springer Publishing Company, Incorporated, New York, NY, 2013. 423 pp.  Type: Book (978-1-447144-01-4)

The challenge in producing an edited collection of papers is to arrive at a volume that is unified, complete, and consistent. The editors of this book have succeeded. It is an excellent summary of the state of theory, technology, and a...

May 15 2013
 
 
 
Display per page
Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright 1999-2024 ThinkLoud®
Terms of Use
| Privacy Policy