Full list is published at:
http://www.guide2research.com/?p=1463

1. [Sat 01 Mar 2014][ScienceDirect] ECAI 2014 : 21st European Conference on Artificial Intelligence
   Prague, Czech Republic – Aug 17, 2014 – Aug 22, 2014
   http://ecai2014.org
2. [Sat 01 Mar 2014][ACM] ICIMCS 2014 : ACM International Conference on Internet Multimedia Computing and Service
   Xiamen, China – Jul 10, 2014 – Jul 12, 2014
   http://icimcs2014.xmu.edu.cn/
3. [Sat 01 Mar 2014][IEEE] ICPP 2014 : International Conference on Parallel Processing
   Minneapolis, USA – Sep 9, 2014 – Sep 12, 2014
   http://icpp.cs.umn.edu/index.php?target=home
4. [Sat 01 Mar 2014][DBLP] SEKE 2014 : 26th International Conference on Software Engineering and Knowledge Engineering
   Vancouver, Canada – Jul 1, 2014 – Jul 3, 2014
   http://www.ksi.edu/seke/seke14.html
5. [Sat 01 Mar 2014][ACM] ICFP 2014 : ACM SIGPLAN International Conference on Functional Programming
   Gothenburg, Sweden – Sep 1, 2014 – Sep 3, 2014
   http://icfpconference.org/icfp2014/
6. [Sat 01 Mar 2014][IEEE] WHISPERS 2014 : 6th IEEE GRSS Workshop on Hyperspectral Image and Signal Processing
   Lausanne, Switzerland – Jun 25, 2014 – Jun 27, 2014
   http://core.ieee-whispers.com/
7. [Sat 01 Mar 2014][IEEE] AVSS 2014 : 11th IEEE International Conference on Advance Video- and Signal-based Surveillance
   Seoul, Korea – Aug 26, 2014 – Aug 29, 2014
   http://avss2014.org/bbs/board.php?bo_table=avss_98
8. [Sat 01 Mar 2014][IEEE] RITMAN 2014 : IEEE WoWMoM Workshop on Resilient Information and Communication Technologies for Management of Natural Disasters
   Sydney, Australia – Jun 16, 2014 – Jun 16, 2014
   http://newslabx.csie.ntu.edu.tw/RITMAN14/
9. [Sat 01 Mar 2014][ACM] DCC 2014 : SIGCOMM Workshop on Distributed Cloud Computing
   Chicago, USA – Aug 22, 2014 – Aug 22, 2014
   https://sites.google.com/site/dcc2014workshop/
10. [Sat 01 Mar 2014][IEEE] ICCI*CC 2014 : 13th IEEE International Conference on Cognitive Informatics & Cognitive Computing
    London, UK – Aug 18, 2014 – Aug 20, 2014
    http://www.ucalgary.ca/icci_cc/ICCICC2014
11. [Sat 01 Mar 2014][ACM] UCDPHA 2014 : 4th International Workshop on User-Centered Design of Pervasive Healthcare Applications 2014
    Oldenburg, Germany – May 20, 2014 – May 20, 2014
    http://www.comm.rwth-aachen.de/pervasivehealth2014/
12. [Sat 01 Mar 2014][IEEE] INDIN 2014 : 12th IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN)
    PORTO ALEGRE RS BRAZIL – Jul 27, 2014 – Jul 30, 2014
    http://www.indin2014.org/
13. [Sat 01 Mar 2014][ACM] DIDC 2014 : The Sixth International Workshop in Data-intensive Distributed Computing in conjunction with HPDC 2014
    Vancouver, Canada – Jun 23, 2014 – Jun 27, 2014
    http://www.fatih.edu.tr/~esma.yildirim/DIDC2014-workshop/home.html
14. [Sat 01 Mar 2014][IEEE] SocialCom 2014 : The Sixth IEEE/ASE International Conference on Social Computing
    Stanford, CA, USA – May 27, 2014 – May 31, 2014
    http://socialcom2014.scienceengineering.org
15. [Sat 01 Mar 2014][ACM] ScienceCloud 2014 : 5th Workshop on Scientific Cloud Computing
    Vancouver, Canada – Apr 4, 2014 – Apr 4, 2014
    http://datasys.cs.iit.edu/events/ScienceCloud2014
16. [Sat 01 Mar 2014][ACM] AsiaCCS SCC 2014 : The Second International Workshop on Security in Cloud Computing
    Kyoto, Japan – Jun 3, 2014 – Jun 3, 2014
    http://conference.cs.cityu.edu.hk/asiaccsscc/
17. ….

The h-index is an index that attempts to measure both the productivity and impact of the published work of a scientist or scholar. The index is based on the set of the scientist’s most cited papers and the number of citations that they have received in other publications. For the list of the scientists having the top H index in the field of Computer Science and Electronics, is listed below:

Source : http://www.guide2research.com/scientists/

1. [151] Herbert Simon

2. [139] Anil K. Jain

3. [121] Terrence Sejnowski

4. [120] Scott Shenker

5. [118] hector garcia-molina

6. [115] Jiawei Han

7. [111] TOMASO POGGIO

8. [111] Sebastian Thrun

9. [111] Ian Foster

10. [109] Michael I. Jordan

11. [106] Andrew Zisserman

12. [106] Georgios B. Giannakis

13. [106] Steven Salzberg

14. [105] Philip S. Yu

15. [105] Wil van der Aalst

16. [104] christos papadimitriou

17. [103] robert tibshirani

18. [103] Alessandro Cerri

19. [101] Jeffrey Ullman

20. [101] Alex Sandy Pentland

21. [101] Sangjin Kim

22. [101] Gunnar von Heijne

Just setup the profile @ Google Scholar at:

http://scholar.google.co.uk/citations?hl=en&user=kudrpNsAAAAJ

Meanwhile, the page for DBLP is located @:

http://www.informatik.uni-trier.de/~ley/pers/hd/b/Bouchrika:Imed

As biometrics can now identify people based on individual measures, it appears prudent to translate these techniques for forensic use. As subjects can conceal features associated with identification, prior convictions have used gait and posture to identify suspect. The locations of human vertices are used within instantaneous posture matching. To derive a measure of confidence in this match, we use an automated analysis to determine the variation in the match measure as a function of increasing database size. We can match subjects between videos and assess the confidence in the match measure. We describe how we can derive a match for suspects recorded performing the same criminal act, in surveillance footage, and assess the confidence. As this is the first study of its kind, it raises many points to consider which can aid refinement not just of the matching procedure, but also constraints on the placement of cameras in surveillance.

We present a new method for view-point independent gait biometrics. The system relies on a single camera, does not require camera calibration and works with a wide range of camera-views. This is achieved by a formulation where the gait is self-calibrating. These properties make the proposed method particularly suitable for identification by gait, where the advantages of completely unobtrusiveness, remoteness and covertness of the biometric system preclude the availability of camera information and specific walking directions. Moreover, tests on the multi-view CASIA-B database, composed of more than 2270 video sequences with 65 different subjects walking freely along different walking directions have been performed. The obtained results show that human identification by gait can be achieved without any knowledge of internal or external camera parameters with a mean CCR of 73.6% using purely dynamic gait features. The performance of the proposed method is particularly encouraging for application in surveillance scenarios.

The simple command to use to convert a given video video.ext to a set of images preferably with the naming format XXXX.png is :

ffmpeg -i video.ext %4d.png

It will produce images with the naming : 0001.png 0002.png and so on. You can try different image format if needed ( Jpeg, bmp…)

In case you want to extract and convert only a specific portion of the video :

ffmpeg -ss hh:mm:ss -t hh:mm:ss -i video.ext %4d.png
-ss option is the starting point whilst -t option is the duration to be converted.

In recent years, automatic visual surveillance  has received considerable interest in the computer vision community. This is due to the increasing numbers of crimes from robbery to terrorist attacks, as well as the inability of human operators to monitor the increasingly growing numbers of surveillance cameras deployed in security sensitive areas such as government buildings and airports, or  public places such as shopping malls and streets. According to the British Security Industry Association, the number of CCTV cameras installed in the UK was estimated to be more than 4.25 million in 2004; this figure is expected to grow rapidly particularly after the terrorist attacks that London witnessed in July 2005.  Despite the huge increase of surveillance systems,  the question whether current surveillance systems work as a deterrent to crime is still debatable. Security systems should not only be able to predict when a crime is about to happen but, more importantly, they ought to identify the individuals suspected of committing crimes, say through the use of biometrics such as gait recognition.