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A University-Industry Collaboration Case Study: Intel Real-Time Multi-View Face Detection Capstone Design Projects
2018
Zenodo
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This paper is a longitudinal case study following three Intel-sponsored multi-view real-time face detection CDP teams with 15 undergraduate students during 2013 and 2014. ...
Engineering specifications and technical outcomes of the multi-view real-time face detection CDPs developed in 3 phases. ...
The post-graduation profile of the 15 students who completed Intel-sponsored real-time multi-view
face detection CDPs. ...
doi:10.5281/zenodo.1227674
fatcat:47fcr7cflzeurhabsljcsld52e
Real-time multi-view face detection and pose estimation based on cost-sensitive AdaBoost
2005
Tsinghua Science and Technology
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In this paper, an integrated method for real-time multi-view face detection and pose estimation is presented. ...
Experimental results show that the proposed multi-view face detector, which can be constructed easily, gives more robust face detection and pose estimation and has a faster real-time detection speed compared ...
[8] have proposed the first real-time multi-view face detection system. In their method, three coarse-to-fine layers of classifiers are designed. ...
doi:10.1016/s1007-0214(05)70047-x
fatcat:hewjsuhoxrentgktpcjw6ih76u
Real-Time Multi-View Face Detection and Pose Estimation in Video Stream
2006
18th International Conference on Pattern Recognition (ICPR'06)
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In this paper, we proposed a solution for real-time multi-view face detection and pose estimation in video stream. ...
Technologies for real-time multi-view face detection from video streams are indispensable to video content-based retrieval systems and video surveillance systems.. ...
Conclusion We have presented a method for real-time multi-view face detection while achieving facial pose estimation. ...
doi:10.1109/icpr.2006.964
dblp:conf/icpr/WangLTX06
fatcat:6vcjiemyunc7rfmvcohgzkd7ha
Real-time multi-view face detection
Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition
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This results in the first real-time multi-view face detection system which runs at 5 frames per second for 320x240 image sequence. ...
In this paper, we present a detector-pyramid architecture for real-time multi-view face detection. Using a coarse to fine strategy, the full view is partitioned into finer and finer views. ...
This leads to the first real-time multi-view face detection system. ...
doi:10.1109/afgr.2002.1004147
dblp:conf/fgr/ZhangZLZ02
fatcat:ftxkdzcgdzafbdtsofe7gqdqyq
Learning to detect multi-view faces in real-time
Proceedings 2nd International Conference on Development and Learning. ICDL 2002
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This work leads to the first real-time multi-view face detection system in the world. It runs at 200 ms per image of size 320x240 pixels on a Pentium-III CPU of 700 MHz. ...
In this paper, we present a system which learns to detect multi-view faces. The system uses a coarse-to-fine, simpleto-complex architecture called detector-pyramid. ...
The system of Schneiderman and Kanade [27] is claimed to be the first algorithm in the world for (non-real-time) multi-view face detection. ...
doi:10.1109/devlrn.2002.1011834
fatcat:fah4l766fzddbfrjnopqrd3c3u
A Novel Multi-view Face Detection Method Based on Improved Real Adaboost Algorithm
2013
KSII Transactions on Internet and Information Systems
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Multi-view face detection has become an active area for research in the last few years. In this paper, a novel multi-view human face detection algorithm based on improved real Adaboost is presented. ...
For frontal face detection, the experiments on MIT+CMU frontal face test set result a 96.4% correct rate with 528 false alarms; for multi-view face in real time test set result a 94.7 % correct rate. ...
Table 3 and Fig. 7 show the experimental results of multi-view face detection. ...
doi:10.3837/tiis.2013.11.010
fatcat:xdjwtl3jnjb4tctb3pqrxx4ske
Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los
...
2017
Advances in Science, Technology and Engineering Systems
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We have worked on the empirical transistor model with a view to describing transistor operation, as well as, ensuring acceptable accuracy. ...
It is also observed that, the device with shorter channel length goes into saturation more rapidly, thereby, reducing the transit time for the charge carriers, which allows the application of the device ...
doi:10.25046/aj0203177
fatcat:qhd2rteuajdqzo77fq74ixwevu
Hardware acceleration of multi-view face detection
2009
2009 IEEE 7th Symposium on Application Specific Processors
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This paper presents a parallelized architecture for hardware acceleration of multi-view face detection. ...
Its performance has been measured and compared with a Jones' and Viola's software implementation of multi-view face detection. ...
face detection in real-time. ...
doi:10.1109/sasp.2009.5226339
dblp:conf/sasp/ChoBK09
fatcat:fc5v7xe2kzbcjhaplojbrmnwqu
Collaborative acquisition of multi-view face images in real-time using a wireless camera network
2011
2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras
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In order to support real-time face recognition using a wireless camera network, we design a data acquisition service to quickly and reliably acquire face images of human subjects from multiple views and ...
In this paper, we describe a collaborative approach in which multi-view camera geometry and inter-camera communication is utilized at run time to significantly reduce the required processing time. ...
TABLE I PROCESSING I TIMES: MULTI-VIEW FACE DETECTION IN CLEAR AND CLUTTERED BACKGROUND ...
doi:10.1109/icdsc.2011.6042898
dblp:conf/icdsc/ParupatiBSK11
fatcat:2rigktlnxve7bbxqwi4psmrwg4
Improved AdaBoost Algorithm for Robust Real-Time Multi-face Detection
2017
Journal of Software
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The human face is detected in real-time environment using the approach called Adaboost-based Haar-Cascade Classifier, and the real human face detection is improved from single-face detection to multi-face ...
Traditional methods are difficult to meet the needs of robust real-time multi face detection because of some influencing factors such as head pose, image scene, illumination condition and so on. ...
Therefore, a robust real-time multi-face detection algorithm with high accuracy is indispensable for the research of face recognition, facial expression recognition, and face attribute analysis, etc. ...
doi:10.17706/jsw.12.1.53-61
fatcat:fbclyjm33vetbaog7r2jrwguka
Improved AdaBoost Algorithm for Face Detection and Its Application
2017
DEStech Transactions on Computer Science and Engineering
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The human face is detected in real time using the approach called AdaBoost-based Haar-Cascade Classifier[1-2], and the real human face detection is improved to implement from single-face detection to multi-face ...
The proposed robot vision algorithm for human detection is tested to be effective and robust through real-time experiments. ...
This approach not only improves the face detection accuracy, but retains the real-time detection speed at the same time. ...
doi:10.12783/dtcse/cmee2016/5362
fatcat:aozdozanxzh3zcocndeuqhrfy4
Real-time and multi-view face tracking on mobile platform
2011
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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In this paper, a multi-view and real-time face tracking system is presented for mobile platform. First, three basic detectors are trained by local binary pattern (LBP) and Boosting algorithm. ...
These detectors are then flexibly expanded for multi-view face detection through the rotation facility of LBP. ...
CONCLUSION In this paper a multi-view and real-time face tracking system is presented. ...
doi:10.1109/icassp.2011.5946774
dblp:conf/icassp/XuLW11
fatcat:a7o3qynlozcuhjterclnmea7me
Multi-view face detection under complex scene based on combined SVMs
2004
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.
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Such combination of SVMs can effectively detect multi-view faces even with large rotation angles and heavy shadow. ...
In this paper, we propose a novel combination of SVMs to detect multi-view faces, using both cascading and bagging methods. In our method, the faces are divided into seven views. ...
false detections "school" 47 44 28 "mall" 58 54 12
Conclusion This paper proposes a combination of SVMs to detect multi-view faces in complex real scenes. ...
doi:10.1109/icpr.2004.1333733
dblp:conf/icpr/WangJ04
fatcat:qlekxktexndexcqpce2v5plzmu
Abstract: Multi-camera, Multi-person, and Real-time Fall Detection using Long Short Term Memory
[chapter]
2021
Informatik aktuell
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Right panel: The view is restricted which underlines the need for multi-camera support. Faces are masked due to the COVID-19 pandemic. ...
We have proposed the following [1]: We augment the human pose estimation algorithm openpifpaf for fall detection by adding multi-camera and multi-person tracking support. ...
Right panel: The view is restricted which underlines the need for multi-camera support. Faces are masked due to the COVID-19 pandemic.
1 Peter L. ...
doi:10.1007/978-3-658-33198-6_29
fatcat:huabha6t6zhjzez7glurlkszly
Multi-view face and eye detection using discriminant features
2007
Computer Vision and Image Understanding
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Multi-view face detection plays an important role in many applications. This paper presents a statistical learning method to extract features and construct classifiers for multi-view face detection. ...
RNDA features are subsequently learned and combined with AdaBoost to form a multi-view face detector. ...
As a result, the frontal face detection achieves the real time, and the multi-view face detection runs at 5 frame per second on the 320 · 240 images on a P4 2.6G processor. ...
doi:10.1016/j.cviu.2006.08.008
fatcat:7r4d47mxerfldlthumfb4eaeeu
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