UNICITY : a depth maps database for people detection in security airlocks

Dumoulin, Joël (School of Engineering and Architecture (HEIA-FR), HES-SO // University of Applied Sciences Western Switzerland) ; Canévet, Olivier (Idiap Research Institute, Martigny, Switzerland) ; Villamizar, Michael (Idiap Research Institute, Martigny, Switzerland) ; Nunes, Hugo (Fastcom Technology SA, Lausanne, Switzerland) ; Abou Khaled, Omar (School of Engineering and Architecture (HEIA-FR), HES-SO // University of Applied Sciences Western Switzerland) ; Mugellini, Elena (School of Engineering and Architecture (HEIA-FR), HES-SO // University of Applied Sciences Western Switzerland) ; Odobez, Jean-Marc (Idiap Research Institute, Martigny, Switzerland) ; Moscheni, Fabrice (x)

We introduce a new dataset, dubbed UNICITY , for the task of detecting people in security airlocks in top view depth images. If security companies have been relying on computer systems and algorithms for a long time, very few are trusting artificial intelligence and more specifically machine learning approaches in production environments. We are confident that the recent advances in these domains, especially with the democratization of deep learning, will open new horizons for security systems. We release this dataset to encourage the development of such approaches in the scientific community. UNICITY consists of 58k images collected from 65 recorded sequences with one or two people performing different behaviors including attacks and trickeries (e.g. tailgating). It also provides full annotation of people such as the location of head and shoulders. As as result, UNICITY is perfectly suited for training and adapting machine learning algorithms for video surveillance applications. This paper presents the data collection, an evaluation protocol, as well as two baseline methods for attack detection.


Conference Type:
full paper
Faculty:
Ingénierie et Architecture
School:
HEIA-FR
Institute:
HumanTech - Technology for Human Wellbeing Institute
Subject(s):
Ingénierie
Publisher:
Auckland, New Zealand, 27-30 November 2018
Date:
2018-11
Auckland, New Zealand
27-30 November 2018
Pagination:
6 p.
Published in:
Proceedings of the 15th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS 2018), 27-30 November 2018, Auckland, New Zealand
Appears in Collection:

Note: The status of this file is: restricted


 Record created 2019-01-22, last modified 2019-01-29

Dumoulin_2018_UNICITY:
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