學術出版;;Publications

Permanent URI for this communityhdl:11536/1

收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

Browse

🏛️國立陽明交通大學機構典藏

Search Results

Now showing 1 - 8 of 8

Fast Multi-View People Localization Using a Torso-High Reference Plane
(2017-01-01)
Hsu, Chun-Chieh
;
Chen, Hua-Tsung
;
Tsai, Wen-Jiin
;
Lee, Suh-Yin
;
交大名義發表
People locations bring rich information for a wide spectrum of applications in intelligent video surveillance systems. In addition to localization accuracy, computational efficiency is another significant issue to be highly concerned in people localization. As an essential early stage, people localization has to be accomplished in a very short time, enabling further semantic analysis. However, most state-of-the-art people localization methods pay little attention to computational efficiency. Hence, in this paper we propose an effective and efficient multi-view people localization scheme with several acceleration mechanisms. First, a torso-high reference plane is introduced since in general the torso part (after foreground segmentation) is more intact and stable than the other parts of a human body, and thus can predict potential people locations more reliably. Then, a novel and computationally efficient bitwise-operation scheme is proposed to predict people locations at the intersection regions of foreground line samples from multiple views. After rule-based validation, people locations can be accurately obtained and visualized on a real world plane. Experiments on multi-view surveillance videos not only validate the high accuracy of the proposed method in locating people under crowded scenes with serious occlusions, but also demonstrate an outstanding computational speed.
Accelerating Vanishing Point-Based Line Sampling Scheme for Real-Time People Localization
(2017-03-01)
Liu, Chin-Wei
;
Chen, Hua-Tsung
;
Lo, Kuo-Hua
;
Wang, Chih-Jung
;
Chuang, Jen-Hui
In advanced video surveillance systems, people localization is usually a part of the complete system and should be accomplished in a short time so as to reserve sufficient processing time for subsequent high-level analysis, such as abnormal event/ behavior detection and intruder detection. Hence, in addition to localization accuracy, computational efficiency is of critical importance as well. In this paper, we adopt a vanishing point-based line sampling scheme and propose a fast multicamera people localization approach capable of locating a crowd of dense people and estimating their heights in a fairly short time with high accuracy. For each camera view, sample lines, originated from a vanishing point, of foreground objects are projected onto the ground plane. Then, people locations are estimated by detecting the ground regions containing a high density of the projected lines. Enhanced from some previous works, the proposed approach does not require processing steps of high computation cost, such as projecting all foreground pixels of all views to multiple reference planes or computing pairwise intersections of projected sample lines at different heights. In addition, some novel acceleration modules, such as torso validation and physical rule-based filtering, are developed to further reduce the computation time of people localization. The experiments on real surveillance scenes validate that the proposed approach achieves significant speedup (up to 186%) over state-of-the-art techniques while still ensure a comparably high localization accuracy, even for crowded scenes with serious occlusions.
1-D Integral Image for Enhancing Efficiency and Effectiveness of Probabilistic Occupancy Map-Based People Localization Approach
(2016)
Lin, Yen-Shuo
;
Chen, Hua-Tsung
;
Hwang, Jenq-Neng
;
Hsiao, Ching-Ju
;
Chuang, Jen-Hui
The popularity of vision-based surveillance systems arouses much research attention in improving the accuracy and efficiency of people localization. Using probabilistic occupancy map (POM) becomes one of the mainstream approaches to people localization due to its great localization accuracy under severe occlusions and lighting changes. However, to enable the usage of rectangular human models and the subsequent 2-D integral image computation, it is assumed that videos are taken at head or eye level. Even so, the computation complexity is still high. Moreover, surveillance videos are often taken from security cameras located at a higher-up location with an oblique viewing angle, so that human models may be quadrilateral and the pixel-based 2-D integral image cannot be utilized. Accordingly, we propose the use of 1-D integral images which are produced for foreground object(s) in an image along equally-spaced line samples originated from the vanishing point of vertical lines (VPVL). Experimental results show that the proposed approach does improve the efficiency and effectiveness of the POM approach in more general camera configurations.
Vanishing Point-Based Image Transforms for Enhancement of Probabilistic Occupancy Map-Based People Localization
(2014-12-01)
Lin, Yen-Shuo
;
Lo, Kuo-Hua
;
Chen, Hua-Tsung
;
Chuang, Jen-Hui
;
資訊工程學系
The widespread use of vision-based surveillance systems has inspired many research efforts on people localization. In this paper, a series of novel image transforms based on the vanishing point of vertical lines is proposed for enhancement of the probabilistic occupancy map (POM)-based people localization scheme. Utilizing the characteristic that the extensions of vertical lines intersect at a vanishing point, the proposed transforms, based on image or ground plane coordinate system, aims at producing transformed images wherein each standing/walking person will have an upright appearance. Thus, the degradation in localization accuracy due to the deviation of camera configuration constraint specified can be alleviated, while the computation efficiency resulted from the applicability of integral image can be retained. Experimental results show that significant improvement in POM-based people localization for more general camera configurations can indeed be achieved with the proposed image transforms.
VP-TRANSFORM: A NOVEL VANISHING POINT-BASED IMAGE TRANSFORM FOR ENHANCEMENT OF PEOPLE LOCALIZATION
(2013-01-01)
Lin, Yen-Shuo
;
Lo, Kuo-Hua
;
Chen, Hua-Tsung
;
Chuang, Jen-Hui
;
資訊工程學系
The widespread use of vision-based surveillance systems has inspires many research efforts on people localization. In this paper, a novel nonlinear image transform based on the vanishing point of vertical lines, entitled VP-transform, is proposed for enhancement of the people localization scheme proposed in [1]. Utilizing the characteristic that the extensions of vertical lines intersect at a vanishing point, the proposed transformation aims at producing rectified images wherein each standing/walking person will have an upright appearance. Thus, the degradation in localization accuracy, due to deviation of the constraint of camera configuration specified in [1], can be alleviated. Experimental results validate the effectiveness of the proposed image transform that significant improvement in people localization can be achieved.
基於多重平面與軸線分析之即時多人定位系統
(2011)
莊仁輝
;
CHUANG JEN-HUI
;
國立交通大學資訊工程學系（所）
以視覺為基礎的人物定位與追蹤的研究中，人物遮蔽是一個重要且具挑戰性的研究課題。在此一研究計畫中，我們提出一多攝影機與多重參考平面的人物定位方法。先前被提出的方法是藉由將多個視角影像中的前景資訊以像素為單位（pixel-based）投影至各參考平面來確認空間中不同高度的參考平面上是否有人物存在，因此比起僅使用單一參考平面，將能夠有效地處理遮蔽之問題。然而將前景像素投影至多重參考平面將耗費大量的計算時間。為了解決上述的問題，我們希望減低投影所需的計算量。在計畫的第一年我們基於消失點對影像中前景區域產生2D樣本線段，並僅將這些2D樣本線段投影至多重參考平面，如此一來可以大幅減少計算時間。後續，我們計算這些2D樣本線段於多重平面上的交點並對這些不同平面的交點進行分析、連接後可形成多條3D的軸線。這些軸線經過評估並淘汰掉不合適的之後，可依據分群的演算法分為數群。各群內的軸線經整合後可重建出人物的位置及身高。
Vanishing Point-based Line Sampling for Real-time People Localization
(2013-07-01)
Lo, Kuo-Hua
;
Chuang, Jen-Hui
;
資訊工程學系
;
Department of Computer Science
In this paper, we propose a real-time multicamera people localization method based on line sampling of image foregrounds. For each view, these line samples are originated from the vanishing point of lines perpendicular to the ground plane. With these line samples, vertical line samples in the 3-D scene can be reconstructed for potential human locations. After some efficient geometric refinement and filtering procedures, the remaining qualified 3-D line samples are clustered and integrated for the identification of locations and heights of people in the scene. Both indoor and outdoor scenarios are examined to demonstrate the effectiveness of our approach in handling serious occlusion in crowed scenes. The average localization error of less than 15 cm for average viewing distance of 15m suggests that our method can be applied to a broad range of surveillance applications that require the real-time computation of localization without using special hardware for acceleration.
VIEW-INVARIANT MEASURE OF LINE CORRESPONDENCE AND ITS APPLICATION IN PEOPLE LOCALIZATION
(2012)
Lo, Kuo-Hua
;
Chuang, Jen-Hui
;
資訊工程學系
;
Department of Computer Science
A correspondence measure of 2D line segments in two different views is proposed in this paper. Such a quantitative measure is view-invariant and can handle line segment of arbitrary configuration in the 3D scene. A line-based people localization scheme is proposed by applying such a measure to improve the efficiency of [1]. By verifying whether 2D line samples from different views belong to the same person, computations associated with incorrectly reconstructed 3D line samples of people can be avoided. Experimental results show that people localization results, in terms of correctness and accuracy, comparable to [1] can be obtained with the proposed scheme, but with more than three times in computation speed.

學術出版;;Publications

Browse

Filters

Settings

Sort By

Results per page

🏛️國立陽明交通大學機構典藏

Search Results