Segmentation and Counting of People Through Collaborative Augmented Environment

Kanchan Warke

Segmentation and Counting of People Through Collaborative Augmented Environment

Kanchan Warke * §

Contact

§ BVDU COE

Segmentation and Counting of People Through Collaborative Augmented Environment

Article Fingerprint

ReserarchID

CSTAO586

Segmentation and Counting of People Through Collaborative Augmented Environment Banner

Key Research Insights

Synthesized scholarly intelligence & interactive research assistant

This converted HTML version may contain rendering inconsistencies. Please refer to the PDF for the authoritative version, or click here to provide feedback.

Abstract

People counting system have wide potential application including video surveillance and public resources management. Also with rapid development of economic society, crowd flowing in varies public places and facility is more and more frequent. Effectively managing and controlling crowd in public places become an important issue. People counting system based on this kind of demand arises, which can be used in commercial domain such as market survey, traffic management as well as architectural design domain. For example suppose there is a crowd gathering at specific place then it indicates an unusual situation and second one if counting of people is done in shopping mall then it provides valuable information for optimizing trading hours, as well as evaluating the attractiveness of some shopping areas.

References

19 Cites in Article

Reference Format

1. S Lin,Y Chen,H Chao (2001). Estimation of number of people in crowded scenes using perspective transformation. IEEE Transactions on Systems, Man and Cybernetics-Part A : Systems and Humans, 3(6), 645-653.
2. T Zhao,R Nevatia (2004). Tracking multiple humans in complex situation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(9), 208-1221.
3. T Zhao,R Nevatia,B Wu (2007). Segmentation and tracking of multiple humans in crowded environment. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(7), 198-1211.
4. Vijay Mahadevan,Nuno Vasconcelos (2008). Background subtraction in highly dynamic scenes. IEEE conference on Computer Vision and Pattern Recognition (CVPR 2008), 6.
5. Wei Di,Rongben Wang (2009). Driver Eyes Identification Based on Infrared Illuminator. 2009 International Conference on Computational Intelligence and Software Engineering, 1-4.
6. Matt Wheeler,M Zmuda (2000). Processing color and complex data using mathematical morphology. Proceedings of the IEEE 2000 National Aerospace and Electronics Conference. NAECON 2000. Engineering Tomorrow (Cat. No.00CH37093), 618-624.
7. Emma Regentova,Shanhram Latifi,Shulan Deng,Yao (2002). An algorithm with reduced operations for connected components detection in ITU-T group 3/4 coded images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(8), 1039-1047.
8. K Terada,D Yoshida,S Oe,J Yamaguchi (1999). A method of counting the passing people by using the stereo images. Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348), 2, 338-342 vol.2.
9. Senem Velipasalar,Ying-Li Tian,Arun Hampapur (2006). Automatic Counting of Interacting People by using a Single Uncalibrated Camera. 2006 IEEE International Conference on Multimedia and Expo, 1265-1268.
10. T Zhao,R Nevatia (2003). Bayesian human segmentation in crowded situations. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2, 459-466.
11. T Zhao,R Nevatia (2004). Tracking multiple humans in crowded environment. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2, 406-413.
12. V Rabaud,S Belongie (2006). Counting Crowded Moving Objects. 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06), 1, 705-711.
13. P Mehta,T Stonham (1996). A system for counting people in video images using neural networks to identify the background scene. Journal of Pattern Recognition, 29(8), 1421-1428.
14. T Schl¨ogl,B Wachmann,H Bischof,W Kropatsch (2003). People counting in complex scenarios. People counting in complex scenarios, 1-8.
15. Antoni Chan,Zhang-Sheng John Liang,Nuno Vasconcelos (2008). Privacy preserving crowd monitoring: Counting people without people models or tracking. 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-7.
16. Dae Kim,Young-Seok Choi (2002). Multimodal Emotion Recognition Based on Global Information Fusion in Conversations. 2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC), 1-5.
17. V Rabaud,S Belongie (2006). Counting Crowded Moving Objects. 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06), 1, 705-711.
18. S Harasse,L Bonnaud,M Desvignes (2005). Human model for people detection in dynamic scenes. 18th International Conference on Pattern Recognition (ICPR'06), 335-354.
19. Dzmitry Tsishkou,Liming Chen,Eugeny Bovbel (2004). Semi-Automatic Ground Truth Annotation for Benchmarking of Face Detection in Video. Semantic-Based Visual Information Retrieval, 107-118.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Kanchan Warke. 1970. "Segmentation and Counting of People Through Collaborative Augmented Environment". Global Journal of Computer Science and Technology GJCST Volume 11 (GJCST Volume 11 Issue 23).

More Citation Formats

Select Citation Style:

Download Citation

GJCST Volume 11 Issue 23

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

architectural commercial domain frequent potential resources

Classification

GJCST Classification H.5.1

I.2.10

Submission ReceivedNovember 7, 2011
Peer Review Double Blind
Handling Editor
Accepted December 6, 2011
Published February 10, 2012

Version of record

v1.2

Issue date

February 10, 2012

Language

English

Order Article Reprint

Experience in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Score: 148

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Akhil Khare,Kanchan Warke,Dr. Akhilesh Upadhayay (PhD/Dr. count: 1)

View Count (all-time): 349

Total Views (Real + Logic): 5919

Total Downloads (simulated): 517

Publish Date: 2011 12, Mon

Monthly Totals (Real + Logic):

Month 1: 59 views
Month 2: 48 views
Month 3: 29 views
Month 4: 33 views
Month 5: 25 views
Month 6: 25 views
Month 7: 31 views
Month 8: 45 views
Month 9: 39 views
Month 10: 42 views
Month 11: 31 views
Month 12: 38 views
Month 13: 36 views
Month 14: 28 views
Month 15: 38 views
Month 16: 18 views
Month 17: 26 views
Month 18: 38 views
Month 19: 24 views
Month 20: 23 views
Month 21: 40 views
Month 22: 34 views
Month 23: 20 views
Month 24: 19 views
Month 25: 42 views
Month 26: 26 views
Month 27: 23 views
Month 28: 34 views
Month 29: 36 views
Month 30: 28 views
Month 31: 25 views
Month 32: 38 views
Month 33: 37 views
Month 34: 27 views
Month 35: 27 views
Month 36: 31 views
Month 37: 27 views
Month 38: 31 views
Month 39: 34 views
Month 40: 32 views
Month 41: 27 views
Month 42: 32 views
Month 43: 23 views
Month 44: 37 views
Month 45: 27 views
Month 46: 43 views
Month 47: 29 views
Month 48: 22 views
Month 49: 38 views
Month 50: 26 views
Month 51: 36 views
Month 52: 43 views
Month 53: 45 views
Month 54: 33 views
Month 55: 40 views
Month 56: 44 views
Month 57: 48 views
Month 58: 32 views
Month 59: 27 views
Month 60: 43 views
Month 61: 30 views
Month 62: 27 views
Month 63: 37 views
Month 64: 28 views
Month 65: 44 views
Month 66: 32 views
Month 67: 30 views
Month 68: 28 views
Month 69: 36 views
Month 70: 28 views
Month 71: 38 views
Month 72: 30 views
Month 73: 40 views
Month 74: 37 views
Month 75: 33 views
Month 76: 29 views
Month 77: 46 views
Month 78: 29 views
Month 79: 41 views
Month 80: 35 views
Month 81: 40 views
Month 82: 26 views
Month 83: 24 views
Month 84: 20 views
Month 85: 16 views
Month 86: 19 views
Month 87: 33 views
Month 88: 36 views
Month 89: 20 views
Month 90: 34 views
Month 91: 32 views
Month 92: 23 views
Month 93: 13 views
Month 94: 39 views
Month 95: 21 views
Month 96: 24 views
Month 97: 25 views
Month 98: 31 views
Month 99: 31 views
Month 100: 44 views
Month 101: 35 views
Month 102: 16 views
Month 103: 25 views
Month 104: 26 views
Month 105: 23 views
Month 106: 32 views
Month 107: 45 views
Month 108: 14 views
Month 109: 46 views
Month 110: 39 views
Month 111: 24 views
Month 112: 31 views
Month 113: 41 views
Month 114: 27 views
Month 115: 37 views
Month 116: 35 views
Month 117: 24 views
Month 118: 41 views
Month 119: 47 views
Month 120: 27 views
Month 121: 31 views
Month 122: 30 views
Month 123: 34 views
Month 124: 41 views
Month 125: 24 views
Month 126: 37 views
Month 127: 30 views
Month 128: 15 views
Month 129: 26 views
Month 130: 32 views
Month 131: 49 views
Month 132: 17 views
Month 133: 27 views
Month 134: 25 views
Month 135: 45 views
Month 136: 24 views
Month 137: 21 views
Month 138: 32 views
Month 139: 36 views
Month 140: 38 views
Month 141: 20 views
Month 142: 41 views
Month 143: 13 views
Month 144: 35 views
Month 145: 19 views
Month 146: 27 views
Month 147: 22 views
Month 148: 27 views
Month 149: 37 views
Month 150: 40 views
Month 151: 26 views
Month 152: 13 views
Month 153: 18 views
Month 154: 31 views
Month 155: 33 views
Month 156: 42 views
Month 157: 35 views
Month 158: 42 views
Month 159: 46 views
Month 160: 34 views
Month 161: 35 views
Month 162: 32 views
Month 163: 40 views
Month 164: 36 views
Month 165: 43 views
Month 166: 31 views
Month 167: 33 views
Month 168: 28 views
Month 169: 20 views
Month 170: 42 views
Month 171: 33 views
Month 172: 27 views
Month 173: 45 views
Month 174: 14 views
Month 175: 46 views
Month 176: 43 views
Month 177: 41 views
Month 178: 62 views
Month 179: 53 views

Total Views: 5.9K

Total Downloads: 517

All Trends