OBJECT COUNTING IN VIDEO SURVEILLANCE USING MULTI-SCALE DENSITY MAP REGRESSION

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Author(s)

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Detail(s)

Original languageEnglish
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing
Subtitle of host publicationProceedings
PublisherIEEE
Pages2422-2426
ISBN (Electronic)9781479981311
ISBN (Print)9781479981328
Publication statusPublished - May 2019

Publication series

NameInternational Conference on Acoustics, Speech, and Signal Processing (ICASSP)
PublisherIEEE
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X

Conference

Title44th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019)
PlaceUnited Kingdom
CityBrighton
Period12 - 17 May 2019

Abstract

In this paper, we present an effective convolutional neural network (CNN) for object counting in video surveillance, namely multi-scale density map regressor (MSDMR). In contrast to existing CNN-based methods that achieve high accuracy by means of empirically increasing the model capacity with more complex structures/layers, we focus on a compact CNN. Specifically, the MSDMR is mainly designed with the supervision of multi-scale outputs, in which two CNN stacks estimate coarse- and fine-scale density maps, respectively. The integral of the fine density map provides the count of objects. The two stacks are connected in a cascaded manner and jointly trained such that the overall model can learn discriminative and complementary features to produce expressive performance. Experimental results show that the proposed MSDMR can achieve higher accuracy compared with state-of-the-art methods on the surveillance datasets.

Research Area(s)

  • Object counting, video surveillance, CNN, density map, multi-scale

Citation Format(s)

OBJECT COUNTING IN VIDEO SURVEILLANCE USING MULTI-SCALE DENSITY MAP REGRESSION. / Wang, Yi; Hou, Junhui; Chau, Lap-Pui.

2019 IEEE International Conference on Acoustics, Speech, and Signal Processing: Proceedings. IEEE, 2019. p. 2422-2426 8683289 (International Conference on Acoustics, Speech, and Signal Processing (ICASSP)).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)