Relevant bibliographies by topics / Non-overlapping cameras

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Non-overlapping cameras'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Non-overlapping cameras.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Non-overlapping cameras"

1

Yin, Lei, Xiangjun Wang, Yubo Ni, Kai Zhou, and Jilong Zhang. "Extrinsic Parameters Calibration Method of Cameras with Non-Overlapping Fields of View in Airborne Remote Sensing." Remote Sensing 10, no. 8 (August 16, 2018): 1298. http://dx.doi.org/10.3390/rs10081298.

Full text
Abstract:
Multi-camera systems are widely used in the fields of airborne remote sensing and unmanned aerial vehicle imaging. The measurement precision of these systems depends on the accuracy of the extrinsic parameters. Therefore, it is important to accurately calibrate the extrinsic parameters between the onboard cameras. Unlike conventional multi-camera calibration methods with a common field of view (FOV), multi-camera calibration without overlapping FOVs has certain difficulties. In this paper, we propose a calibration method for a multi-camera system without common FOVs, which is used on aero photogrammetry. First, the extrinsic parameters of any two cameras in a multi-camera system is calibrated, and the extrinsic matrix is optimized by the re-projection error. Then, the extrinsic parameters of each camera are unified to the system reference coordinate system by using the global optimization method. A simulation experiment and a physical verification experiment are designed for the theoretical arithmetic. The experimental results show that this method is operable. The rotation error angle of the camera’s extrinsic parameters is less than 0.001rad and the translation error is less than 0.08 mm.
APA, Harvard, Vancouver, ISO, and other styles
2

Van Crombrugge, Izaak, Rudi Penne, and Steve Vanlanduit. "Extrinsic camera calibration for non-overlapping cameras with Gray code projection." Optics and Lasers in Engineering 134 (November 2020): 106305. http://dx.doi.org/10.1016/j.optlaseng.2020.106305.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Lv, Rui Peng, Hai Gang Sui, Ji Hui Tu, Xiao Yu Cai, and Liang Dong. "Object Tracking across Non-Overlapping Cameras Based on Improved TLD and Multi-Feathers Object Matching." Applied Mechanics and Materials 602-605 (August 2014): 1713–17. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1713.

Full text
Abstract:
Object tracking across non-overlapping views is a hot and important research topic in compute vision. In this paper, a novel method to track the interested object continuously across non-overlapping cameras is presented. This challenging task is taken as two sub-problems: single camera object tracking and object matching across disjoint cameras. An object tracking algorithm which improves Tracking-Learning-Detection (TLD) algorithm by adding background extraction and Kalman filter is presented to deal with the first problem. A new object matching algorithm based on the fusion of global features and local features at the assistance of 3D GIS is also introduced for object matching across disjoint cameras. The proposed approach does not need a training phase and inter-camera calibration. Experiments are carried out on real world videos to validate the proposed approach.
APA, Harvard, Vancouver, ISO, and other styles
4

Hanel, A., and U. Stilla. "STRUCTURE-FROM-MOTION FOR CALIBRATION OF A VEHICLE CAMERA SYSTEM WITH NON-OVERLAPPING FIELDS-OF-VIEW IN AN URBAN ENVIRONMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 181–88. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-181-2017.

Full text
Abstract:
Vehicle environment cameras observing traffic participants in the area around a car and interior cameras observing the car driver are important data sources for driver intention recognition algorithms. To combine information from both camera groups, a camera system calibration can be performed. Typically, there is no overlapping field-of-view between environment and interior cameras. Often no marked reference points are available in environments, which are a large enough to cover a car for the system calibration. In this contribution, a calibration method for a vehicle camera system with non-overlapping camera groups in an urban environment is described. A-priori images of an urban calibration environment taken with an external camera are processed with the structure-frommotion method to obtain an environment point cloud. Images of the vehicle interior, taken also with an external camera, are processed to obtain an interior point cloud. Both point clouds are tied to each other with images of both image sets showing the same real-world objects. The point clouds are transformed into a self-defined vehicle coordinate system describing the vehicle movement. On demand, videos can be recorded with the vehicle cameras in a calibration drive. Poses of vehicle environment cameras and interior cameras are estimated separately using ground control points from the respective point cloud. All poses of a vehicle camera estimated for different video frames are optimized in a bundle adjustment. In an experiment, a point cloud is created from images of an underground car park, as well as a point cloud of the interior of a Volkswagen test car is created. Videos of two environment and one interior cameras are recorded. Results show, that the vehicle camera poses are estimated successfully especially when the car is not moving. Position standard deviations in the centimeter range can be achieved for all vehicle cameras. Relative distances between the vehicle cameras deviate between one and ten centimeters from tachymeter reference measurements.
APA, Harvard, Vancouver, ISO, and other styles
5

LIU, Shao-hua, Mao-jun ZHANG, and Wang CHEN. "Data association algorithm of multiple non-overlapping cameras." Journal of Computer Applications 29, no. 9 (November 13, 2009): 2378–82. http://dx.doi.org/10.3724/sp.j.1087.2009.02378.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Cheng, De, Yihong Gong, Jinjun Wang, Qiqi Hou, and Nanning Zheng. "Part-aware trajectories association across non-overlapping uncalibrated cameras." Neurocomputing 230 (March 2017): 30–39. http://dx.doi.org/10.1016/j.neucom.2016.11.038.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Lee, Young-Gun, Zheng Tang, and Jenq-Neng Hwang. "Online-Learning-Based Human Tracking Across Non-Overlapping Cameras." IEEE Transactions on Circuits and Systems for Video Technology 28, no. 10 (October 2018): 2870–83. http://dx.doi.org/10.1109/tcsvt.2017.2707399.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Ukita, Norimichi, Yusuke Moriguchi, and Norihiro Hagita. "People re-identification across non-overlapping cameras using group features." Computer Vision and Image Understanding 144 (March 2016): 228–36. http://dx.doi.org/10.1016/j.cviu.2015.06.011.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Xia, Renbo, Maobang Hu, Jibin Zhao, Songlin Chen, Yueling Chen, and ShengPeng Fu. "Global calibration of non-overlapping cameras: State of the art." Optik 158 (April 2018): 951–61. http://dx.doi.org/10.1016/j.ijleo.2017.12.159.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

KAWASAKI, Atsushi, Kosuke HARA, and Hideo SAITO. "Line-Based SLAM Using Non-Overlapping Cameras in an Urban Environment." IEICE Transactions on Information and Systems E101.D, no. 5 (May 1, 2018): 1232–42. http://dx.doi.org/10.1587/transinf.2017mvp0006.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Non-overlapping cameras"

1

Nilsson, Henrik. "Evaluation of Methods for Person Re-identification between Non-overlapping Surveillance Cameras." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177889.

Full text
Abstract:
This thesis describes a comparison of several state-of-the-art methods used for re-identification of a person between several non-overlapping views captured by surveillance cameras. Since 2014, the focus of the area of person re-identification has been heavily oriented towards approaches employing the use of neural network due to the increase in performance shown from this approach. Three different methods employing convolutional neural networks as a means of attempting automatic person re-identification have mainly been evaluated in this thesis. These three methods are named Spatial-Temporal Person Re-identification (ST-reID), Top DropBlock Network (Top-DB-Net), and Adaptive L2 Regularization. A fourth method known as Multiple Expert Brainstorming Network (MEB-Net) using domain adaptation is used for comparison to the results of applying the trained models from the other three methods on an unseen environment. As an attempt at improving the results of applying the models on an unseen environment, two different approaches have been taken. The first of these is an attempt at segmenting the person from the background by creating a mask that encapsulates the person while disregarding the background, as opposed to using a rectangular cropped image for training and evaluating the methods. To do this, Mask-RCNN which is a framework for object instance segmentation is used. The second approach explored in this thesis is attempting automatic white balancing as a means of removing the effect of the illumination source of the scenes before the person images are extracted. Both approaches show positive results when the model is applied on an unseen environment as opposed to using the unchanged person images, although the results have not been able to match those that have been obtained using domain adaptation.

Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet

APA, Harvard, Vancouver, ISO, and other styles
2

Lébraly, Pierre. "Etalonnage de caméras à champs disjoints et reconstruction 3D : Application à un robot mobile." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2012. http://tel.archives-ouvertes.fr/tel-00795259.

Full text
Abstract:
Ces travaux s'inscrivent dans le cadre du projet VIPA " Véhicule Individuel Public Autonome ", au cours duquel le LASMEA et ses partenaires ont mis au point des véhicules capables de naviguer automatiquement, sans aucune infrastructure extérieure dédiée, dans des zones urbaines (parkings, zones piétonnes, aéroports). Il est doté de deux caméras, l'une à l'avant, et l'autre à l'arrière. Avant son déploiement, le véhicule doit tout d'abord être étalonné et conduit manuellement afin de reconstruire la carte d'amers visuels dans laquelle il naviguera ensuite automatiquement. Les travaux de cette thèse ont pour but de développer et de mettre en oeuvre des méthodes souples permettant d'étalonner cet ensemble de caméras dont les champs de vue sont totalement disjoints. Après une étape préalable d'étalonnage intrinsèque et un état de l'art sur les systèmes multi-caméra, nous développons et mettons en oeuvre différentes méthodes d'étalonnage extrinsèque (déterminant les poses relatives des caméras à champs de vue disjoints). La première méthode présentée utilise un miroir plan pour créer un champ de vision commun aux différentes caméras. La seconde approche consiste à manoeuvrer le véhicule pendant que chaque caméra observe une scène statique composée de cibles (dont la détection est sous-pixellique). Dans la troisième approche, nous montrons que l'étalonnage extrinsèque peut être obtenu simultanément à la reconstruction 3D (par exemple lors de la phase d'apprentissage), en utilisant des points d'intérêt comme amers visuels. Pour cela un algorithme d'ajustement de faisceaux multi-caméra a été développé avec une implémentation creuse. Enfin, nous terminons par un étalonnage déterminant l'orientation du système multi-caméra par rapport au véhicule.
APA, Harvard, Vancouver, ISO, and other styles
3

Kim, Jae-Hak, and Jae-Hak Kim@anu edu au. "Camera Motion Estimation for Multi-Camera Systems." The Australian National University. Research School of Information Sciences and Engineering, 2008. http://thesis.anu.edu.au./public/adt-ANU20081211.011120.

Full text
Abstract:
The estimation of motion of multi-camera systems is one of the most important tasks in computer vision research. Recently, some issues have been raised about general camera models and multi-camera systems. Using many cameras as a single camera is studied [60], and the epipolar geometry constraints of general camera models is theoretically derived. Methods for calibration, including a self-calibration method for general camera models, are studied [78, 62]. Multi-camera systems are an example of practically implementable general camera models and they are widely used in many applications nowadays because of both the low cost of digital charge-coupled device (CCD) cameras and the high resolution of multiple images from the wide field of views. To our knowledge, no research has been conducted on the relative motion of multi-camera systems with non-overlapping views to obtain a geometrically optimal solution. ¶ In this thesis, we solve the camera motion problem for multi-camera systems by using linear methods and convex optimization techniques, and we make five substantial and original contributions to the field of computer vision. First, we focus on the problem of translational motion of omnidirectional cameras, which are multi-camera systems, and present a constrained minimization method to obtain robust estimation results. Given known rotation, we show that bilinear and trilinear relations can be used to build a system of linear equations, and singular value decomposition (SVD) is used to solve the equations. Second, we present a linear method that estimates the relative motion of generalized cameras, in particular, in the case of non-overlapping views. We also present four types of generalized cameras, which can be solvable using our proposed, modified SVD method. This is the first study finding linear relations for certain types of generalized cameras and performing experiments using our proposed linear method. Third, we present a linear 6-point method (5 points from the same camera and 1 point from another camera) that estimates the relative motion of multi-camera systems, where cameras have no overlapping views. In addition, we discuss the theoretical and geometric analyses of multi-camera systems as well as certain critical configurations where the scale of translation cannot be determined. Fourth, we develop a global solution under an L∞ norm error for the relative motion problem of multi-camera systems using second-order cone programming. Finally, we present a fast searching method to obtain a global solution under an L∞ norm error for the relative motion problem of multi-camera systems, with non-overlapping views, using a branch-and-bound algorithm and linear programming (LP). By testing the feasibility of LP at the earlier stage, we reduced the time of computation of solving LP.¶ We tested our proposed methods by performing experiments with synthetic and real data. The Ladybug2 camera, for example, was used in the experiment on estimation of the translation of omnidirectional cameras and in the estimation of the relative motion of non-overlapping multi-camera systems. These experiments showed that a global solution using L∞ to estimate the relative motion of multi-camera systems could be achieved.
APA, Harvard, Vancouver, ISO, and other styles
4

Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.

Full text
Abstract:
Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.
APA, Harvard, Vancouver, ISO, and other styles
5

Wu, Chen-Shien, and 吳俊賢. "Humans Tracking across Multiple Cameras with Non-overlapping Views." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/85098594589373587588.

Full text
Abstract:
碩士
國立成功大學
電腦與通信工程研究所
97
Human tracking plays an important role in visual surveillance systems. Spatial-temporal movement and appearance of human provide significant visual cues to perform human tracking. We propose a method to estimate human transition probability across different views by a learning architecture. In the learning phase, we first use the prior knowledge to build the observed zones for each camera. Then, human tracking is performed to record the zones of the observed region where humans enter and leave. We use hidden Markov model (HMM) to learn the transition probability between observed zones. The time information such as the sequence of zone human moves is also imposed in HMM. In the testing phase, we present multi-camera tracking algorithm to perform correspondences between humans using the maximum a posteriori estimation framework by the human transition topology and appearance model. The parameters learned in the training phase will be updated with the incoming tracking results. We will show the experiment result using real world surveillance videos to evaluate our method.
APA, Harvard, Vancouver, ISO, and other styles
6

Chen, Chih-Chiang, and 陳志強. "Multiple Object Tracking and Identification Using Non-Overlapping Multiple Cameras." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/90539407115467425219.

Full text
Abstract:
碩士
元智大學
電機工程學系
96
Object tracking and identification play an important role in many multimedia processes. This paper proposes a novel approach for pedestrians analyzing and tracking between multiple non-overlapping cameras. Traditional methods tried to analyze and track pedestrians between multiple cameras using their color transformation. However, the color feature is unstable under different lighting conditions and especially will change when the view is changed to another one. In addition, lots of training data are required for training the color transformation between views. To tackle the above problems, this paper proposes a framework which includes not only the spatial model but also the temporal features for well analyzing pedestrians even though they are observed under two non-overlapping cameras. In the spatial model, the appearance and geometry feature of pedestrians are included for extracting their invariant properties among different camera views. To reduce the effects of illumination change, instead of modeling the whole body, a component-based scheme is proposed for modeling a pedestrian’s appearances up to his body parts. In temporal model, we use speed and probability information between views as our measuring features. Experimental results reveal the performances of our system in several different conditions.
APA, Harvard, Vancouver, ISO, and other styles
7

Chin-TsungHung and 洪晉宗. "People Identification across Non-Overlapping Cameras in Spatial and Temporal Domain." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/83659898121183897472.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Chen, Ke-Yin, and 陳科引. "Human Tracking using Augmented Feature Propagation for Multiple Cameras with Non-overlapping Views." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/27528348497112995914.

Full text
Abstract:
碩士
國立清華大學
電機工程學系
99
Due to tremendous amount of crime activities have occurred recently, Security has become the important issue. Surveillance systems have been installed in home, airports, railway stations, department stores and other places. The traditional surveillance systems have required high human cost but with low efficiency. Therefore, new types of multi-camera surveillance system can automatically detect and continuously track the moving objects based on computer vision technology. Under some circumstances, the tracking of human objects may fail because of light change, unusual behaviors, clothes change between cameras, or staying in the blind region for a long time. It will generate path discontinuity. In this thesis, we make use of the relaxed features matching to solve the problem of missing object tracking. Furthermore, because of the viewing angle of the cameras or the objects’ moving directions are different, the captured features are not the same. We propose a concept indicating that the feature can be propagated between different scenes. The augmented feature can be used for cascading the objects paths. We propose Augmented Feature to correct the path by using the similar appearance of the objects across multiple cameras.
APA, Harvard, Vancouver, ISO, and other styles
9

CHI, JUI-YANG, and 紀瑞洋. "Fast Object Tracking Algorithm and Embedded System Design from Non-Overlapping Multiple Cameras." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/9nq64v.

Full text
Abstract:
碩士
國立雲林科技大學
電子工程系
105
In this paper, we propose a multi-camera object tracking method, which contains two method: the color correction for multi-camera and the topology of the camera. In the algorithm, we propose a visual channel calculation method suitable for multi-camera. This method can solve the problem of color difference and different light sources between cameras. In order to enhance the accuracy of the object re-identification between multi-camera. We set the topology map according to the camera, which can make the algorithm get better performance. The proposed method is evaluated through a wide range of experimental databases. The results show that the proposed method can improve the performance of non-overlapping multi-camera object tracking. Because we propose a method suitable for embedded systems, so the algorithm is designed for hardware and software architecture and implemented in System on Chip. The algorithm is real time for processing on the SoC development board
APA, Harvard, Vancouver, ISO, and other styles
10

Huang, Shu-jung, and 黃姝蓉. "A Target Tracking Approach to the Same Moving Objects across Non-overlapping Multi-cameras." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/38328602681694975162.

Full text
Abstract:
碩士
國立臺灣科技大學
資訊工程系
101
Due to single camera finite surveillance, using amount of overlapping multi-cameras to monitor region cannot satisfy the demand of wide region video surveillance in the considerations of economic and computational aspects. In recent years, messages transformation and fusion of moving object in non-overlapping multi-cameras have become popular research in video surveillance. The difficult part of target tracking in non-overlapping multi-cameras is the spatial discontinuous of cameras, the difference of setting angles and environment of camera. Besides, people are non-rigid objects; it’s difficult for cameras to do object matching because of the external condition and the inherent psychological impact. In this thesis, we propose an integrated system by using non-overlapping multi-cameras for different brightness and viewing angles environments to long-range tack object. The first thing is to detect the moving objects by Gaussian Mixture Model (GMM), shadow removal and morphological etc. preprocess, and then adoptive blob intersection to track moving objects. In order to deal with the objects occlusion case , we use mean shift algorithm with Kalman filter to track these moving objects. In training phase, setting up the link relation of cameras manually by the observer and using a number of known pair objects across different field of views continuously to statistics and estimate the Gaussian distribution of travel time of the objects across blind region, and further obtain the maximum/minimum travel time of the object moving through the blind region, and using cumulative BTF to get the brightness relation between different field of views. After calibrating the color of object by BTF, extract the major color of object to be the feature of object ; then combine the estimated time relation to select likely objects and match the feature of objects. For the experiment part, we use the scenes of different illustration and view angle to analyze, such as two cameras set indoor hallway and outdoor square, three cameras set indoor hallway. The system based on the proposed method can identify objects with the accuracy of 97.5% for two cameras set indoor hallway, 94.4% set outdoor square, and 94.6% for three cameras set indoor hallway. The frame rate is about 15 to 30 fps.
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Non-overlapping cameras"

1

Lee, Kyoung-Mi. "Intelligent Tracking Persons Through Non-overlapping Cameras." In Lecture Notes in Computer Science, 733–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11538356_76.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Chen, Xiaotang, Kaiqi Huang, and Tieniu Tan. "Object Tracking across Non-overlapping Cameras Using Adaptive Models." In Computer Vision - ACCV 2012 Workshops, 464–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37484-5_38.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Robinson, Andreas, Mikael Persson, and Michael Felsberg. "Robust Accurate Extrinsic Calibration of Static Non-overlapping Cameras." In Computer Analysis of Images and Patterns, 342–53. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64698-5_29.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Han, Minho, and Ikkyun Kim. "Hue Modeling for Object Tracking in Multiple Non-overlapping Cameras." In Lecture Notes in Computer Science, 69–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-44949-9_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Gao, Wen Jun Calvin, Poh Say Keong, and Bingquan Shen. "Human Attribute Classification for Re-identification Across Non-overlapping Cameras." In IRC-SET 2018, 75–86. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9828-6_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Taj, Murtaza, Ali Hassan, and Abdul Rafay Khalid. "2D Human Pose Estimation and Tracking in Non-overlapping Cameras." In Human Behavior Understanding in Networked Sensing, 261–81. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10807-0_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Santiago Ramírez, Everardo, J. C. Acosta-Guadarrama, Jose Manuel Mejía Muñoz, Josue Dominguez Guerrero, and J. A. Gonzalez-Fraga. "Facial Re-identification on Non-overlapping Cameras and in Uncontrolled Environments." In Lecture Notes in Computer Science, 170–82. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21077-9_16.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Truong Cong, Dung Nghi, Catherine Achard, Louahdi Khoudour, and Lounis Douadi. "Video Sequences Association for People Re-identification across Multiple Non-overlapping Cameras." In Image Analysis and Processing – ICIAP 2009, 179–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04146-4_21.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Iguernaissi, Rabah, Djamal Merad, and Pierre Drap. "People’s Re-identification Across Multiple Non-overlapping Cameras by Local Discriminative Patch Matching." In Lecture Notes in Computer Science, 190–97. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59876-5_22.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Mazzeo, Pier Luigi, Paolo Spagnolo, and Tiziana D’Orazio. "Object Tracking by Non-overlapping Distributed Camera Network." In Advanced Concepts for Intelligent Vision Systems, 516–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04697-1_48.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Non-overlapping cameras"

1

Zou, Wuhe, and Shigang Li. "Calibrating Non-overlapping RGB-D Cameras." In 2014 22nd International Conference on Pattern Recognition (ICPR). IEEE, 2014. http://dx.doi.org/10.1109/icpr.2014.720.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Shiva Kumar, K. A., K. R. Ramakrishnan, and G. N. Rathna. "Inter-Camera Person Tracking in Non-overlapping Networks." In ICDSC 2017: International Conference on Distributed Smart Cameras. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3131885.3131912.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Lebraly, Pierre, Eric Royer, Omar Ait-Aider, Clement Deymier, and Michel Dhome. "Fast calibration of embedded non-overlapping cameras." In 2011 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2011. http://dx.doi.org/10.1109/icra.2011.5979743.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Anjum, Nadeem, Murtaza Taj, and Andrea Cavallaro. "Relative Position Estimation of Non-Overlapping Cameras." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.366227.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Pagel, Frank. "Calibration of non-overlapping cameras in vehicles." In 2010 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2010. http://dx.doi.org/10.1109/ivs.2010.5547991.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Sonbhadra, Sanjay Kumar, Sonali Agarwal, Mohammad Syafrullah, and Krisna Adiyarta. "Person tracking with non-overlapping multiple cameras." In 2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI). IEEE, 2020. http://dx.doi.org/10.23919/eecsi50503.2020.9251869.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Cohen, Isaac, Yunqian Ma, and Ben Miller. "Tracking moving objects across non-overlapping cameras." In Optics/Photonics in Security and Defence, edited by Colin Lewis. SPIE, 2007. http://dx.doi.org/10.1117/12.737648.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Jayamanne, Dileepa Joseph, and Ranga Rodrigo. "Establishing object correspondence across non-overlapping calibrated cameras." In 2015 Moratuwa Engineering Research Conference (MERCon). IEEE, 2015. http://dx.doi.org/10.1109/mercon.2015.7112337.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Cai, Yinghao, Kaiqi Huang, and Tieniu Tan. "Human appearance matching across multiple non-overlapping cameras." In 2008 19th International Conference on Pattern Recognition (ICPR). IEEE, 2008. http://dx.doi.org/10.1109/icpr.2008.4761704.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Xu, Hang, Yanning Guo, Zhen Feng, and Zhen Chen. "Visual Odometry Using Non-Overlapping RGB-D Cameras." In 2019 Chinese Automation Congress (CAC). IEEE, 2019. http://dx.doi.org/10.1109/cac48633.2019.8997496.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Non-overlapping cameras' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography