Silhouette representation and matching for 3D pose discrimination – A comparative study

Chen, Cheng; Zhuang, Yueting; Xiao, Jun

doi:10.1016/j.imavis.2009.10.008

Cited by 10 publications

(4 citation statements)

References 76 publications

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“…This is also the case for systems designed for observation and deduction based on human silhouette detection and pose estimation. A good overview of silhouette representation is proposed by Chen et al in [ 14 ]. Such an approach is used in the crowd density management system proposed by Velastin et al [ 15 ] and the congestion detection system proposed by Lo et al [ 16 ].…”

Section: Related Workmentioning

confidence: 99%

Automated Detection of Firearms and Knives in a CCTV Image

Grega

Matiolański

Guzik

et al. 2016

Sensors

146

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Closed circuit television systems (CCTV) are becoming more and more popular and are being deployed in many offices, housing estates and in most public spaces. Monitoring systems have been implemented in many European and American cities. This makes for an enormous load for the CCTV operators, as the number of camera views a single operator can monitor is limited by human factors. In this paper, we focus on the task of automated detection and recognition of dangerous situations for CCTV systems. We propose algorithms that are able to alert the human operator when a firearm or knife is visible in the image. We have focused on limiting the number of false alarms in order to allow for a real-life application of the system. The specificity and sensitivity of the knife detection are significantly better than others published recently. We have also managed to propose a version of a firearm detection algorithm that offers a near-zero rate of false alarms. We have shown that it is possible to create a system that is capable of an early warning in a dangerous situation, which may lead to faster and more effective response times and a reduction in the number of potential victims.

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Section: Related Workmentioning

confidence: 99%

Automated Detection of Firearms and Knives in a CCTV Image

Grega

Matiolański

Guzik

et al. 2016

Sensors

146

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“…These methods estimate the 2D or 3D positions of human key points (e.g., joints) from only RGB images or movies. CV studies capitalizing on such pose estimation methods enabled researchers to easily quantify human postures or body movements [24][25][26]. In the past several years, CV techniques have been applied to medical fields which include, for example, diagnosis of autism spectrum disorder [27,28] or detection of gait abnormalities [29].…”

Section: Introductionmentioning

confidence: 99%

Computer Vision-Based Approach for Quantifying Occupational Therapists’ Qualitative Evaluations of Postural Control

Hagihara

Ienaga

Enomoto

et al. 2020

Occupational Therapy International

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This study aimed to leverage computer vision (CV) technology to develop a technique for quantifying postural control. A conventional quantitative index, occupational therapists’ qualitative clinical evaluations, and CV-based quantitative indices using an image analysis algorithm were applied to evaluate the postural control of 34 typically developed preschoolers. The effectiveness of the CV-based indices was investigated relative to current methods to explore the clinical applicability of the proposed method. The capacity of the CV-based indices to reflect therapists’ qualitative evaluations was confirmed. Furthermore, compared to the conventional quantitative index, the CV-based indices provided more detailed quantitative information with lower costs. CV-based evaluations enable therapists to quantify details of motor performance that are currently observed qualitatively. The development of such precise quantification methods will improve the science and practice of occupational therapy and allow therapists to perform to their full potential.

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“…The effectiveness of our approach is validated quantitatively through extensive 34 evaluations on both synthetic and real data, and qualitatively by inspecting the results of the real time 35 system we have implemented. 36 Ó 2010 Elsevier Inc. All rights reserved. to retrieve a set of pose candidates.…”

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confidence: 99%

“…4. This is clearly more difficult 1 Many other evaluations [42,36] use the same configuration, where the testing partition is not used because ground-truth is not available. 2 Actually, we could still use the silhouette-based features as in Section 5.1 and get similar results.…”

mentioning

confidence: 99%