scholarly journals Person Detection from Overhead View: A Survey

Author(s):  
Misbah Ahmad ◽  
Imran Ahmed ◽  
Kaleem Ullah ◽  
Iqbal khan ◽  
Ayesha Khattak ◽  
...  
2014 ◽  
Author(s):  
Jamie L. Gorman ◽  
Kent D. Harber ◽  
Maggie Shiffrar ◽  
Karen Quigley
Keyword(s):  

2019 ◽  
Vol 2019 (11) ◽  
pp. 268-1-268-9
Author(s):  
Herman G.J Groot ◽  
Egor Bondarev ◽  
Peter H.N. de With

2020 ◽  
Vol 71 (7) ◽  
pp. 868-880
Author(s):  
Nguyen Hong-Quan ◽  
Nguyen Thuy-Binh ◽  
Tran Duc-Long ◽  
Le Thi-Lan

Along with the strong development of camera networks, a video analysis system has been become more and more popular and has been applied in various practical applications. In this paper, we focus on person re-identification (person ReID) task that is a crucial step of video analysis systems. The purpose of person ReID is to associate multiple images of a given person when moving in a non-overlapping camera network. Many efforts have been made to person ReID. However, most of studies on person ReID only deal with well-alignment bounding boxes which are detected manually and considered as the perfect inputs for person ReID. In fact, when building a fully automated person ReID system the quality of the two previous steps that are person detection and tracking may have a strong effect on the person ReID performance. The contribution of this paper are two-folds. First, a unified framework for person ReID based on deep learning models is proposed. In this framework, the coupling of a deep neural network for person detection and a deep-learning-based tracking method is used. Besides, features extracted from an improved ResNet architecture are proposed for person representation to achieve a higher ReID accuracy. Second, our self-built dataset is introduced and employed for evaluation of all three steps in the fully automated person ReID framework.


Circulation ◽  
2015 ◽  
Vol 131 (suppl_2) ◽  
Author(s):  
Masako Fujiwara ◽  
Tohru Kobayashi ◽  
Satoko Tsuru ◽  
Hiroyuki Ida

Background: In Japan, 2 guidelines are published, the clinical guidelines for medical treatment of acute stage Kawasaki disease(KD)(2012) and guidelines for diagnosis and management of cardiovascular sequelae in KD(2013). Patient Condition Adaptive Path System (PCAPS) is a technique to structure clinical knowledge. It places “patient condition” as a core, to which multiple “target conditions” are linked. On the other hand, patients of KD ware focused the severity of the disease and therapeutic strategy influences the improvement. Purpose: The purpose is confirming the PCAPS KD contents, which complied two Japanese Guidelines and to evaluate adaption of the contents. Methods: PCAPS content is composed of Clinical Process Chart (CPC) and Unit Sheet (US).CPC is an overhead view of clinical path consisting of a chain of units. CPC was made according the guidelines, and coronary evaluation, CHF, cardiac catheterization and ACS unit can activate on time. CPC stratify the patient’s severity. US are composed of specific healthcare tasks in a unit. Results: We confirm PCAPS KD contents on the base of 2 guidelines. We can evaluate diagnostic process and severity of KD by route analysis using CPC (figure). We can visualize relationship between treatments and severity by US. US are effective to support the decision on treatment and examinations. From the analysis, there are no lack of the unit and route, and confirm the advice to decision making. Conclusions: PCAPS can easily analyze the severity and clinical process from CPC route analysis because PCAPS is electrical path which can automatically store the data of each hospital. From US data, there are possibilities to find new severity score.


2019 ◽  
Vol 87 ◽  
pp. 170-178 ◽  
Author(s):  
Federico Bartoli ◽  
Giuseppe Lisanti ◽  
Svebor Karaman ◽  
Alberto Del Bimbo
Keyword(s):  

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