18.3.1.1 Event Camera

Chapter Contents (Back)
Event Camera. Motion, Differencing. Reports events of significant pixel intensity changes.

Barranco, F.[Francisco], Fermuller, C., Aloimonos, Y.,
Contour Motion Estimation for Asynchronous Event-Driven Cameras,
PIEEE(102), No. 10, October 2014, pp. 1537-1556.
IEEE DOI 1410
computer vision BibRef

Barranco, F.[Francisco], Teo, C.L., Fermuller, C., Aloimonos, Y.,
Contour Detection and Characterization for Asynchronous Event Sensors,
ICCV15(486-494)
IEEE DOI 1602
Computer vision BibRef

Liu, H.C.[Han-Chao], Zhang, F.L.[Fang-Lue], Marshall, D.[David], Shi, L.P.[Lu-Ping], Hu, S.M.[Shi-Min],
High-speed video generation with an event camera,
VC(33), No. 6-8, June 2017, pp. 749-759.
Springer DOI 1706
Only record events when the light on a pixel changes. Good for high speed images, but incomplete data. BibRef

Munda, G.[Gottfried], Reinbacher, C.[Christian], Pock, T.[Thomas],
Real-Time Intensity-Image Reconstruction for Event Cameras Using Manifold Regularisation,
IJCV(126), No. 12, December 2018, pp. 1381-1393.
Springer DOI 1811
BibRef

Reinbacher, C.[Christian], Graber, G.[Gottfried], Pock, T.[Thomas],
Real-Time Intensity-Image Reconstruction for Event Cameras Using Manifold Regularisation,
BMVC16(xx-yy).
DOI Link 1805
From per-pixel intensity changes, not intensity level. The inverse of change detection. BibRef

Gallego, G.[Guillermo], Lund, J.E.A.[Jon E.A.], Mueggler, E.[Elias], Rebecq, H.[Henri], Delbruck, T.[Tobi], Scaramuzza, D.[Davide],
Event-Based, 6-DOF Camera Tracking from Photometric Depth Maps,
PAMI(40), No. 10, October 2018, pp. 2402-2412.
IEEE DOI 1809
Cameras, Standards, Tracking, Voltage control, Robot vision systems, Event-based vision, pose tracking, dynamic vision sensor, AR/VR BibRef

Rebecq, H.[Henri], Gallego, G.[Guillermo], Scaramuzza, D.[Davide],
EMVS: Event-based Multi-View Stereo,
BMVC16(xx-yy).
HTML Version. 1805
Stereo with event (pixel change, not value) cameras. BibRef

Rebecq, H.[Henri], Ranftl, R.[Rene], Koltun, V.[Vladlen], Scaramuzza, D.[Davide],
High Speed and High Dynamic Range Video with an Event Camera,
To Appear, PAMI,
Earlier:
Events-To-Video: Bringing Modern Computer Vision to Event Cameras,
CVPR19(3852-3861).
IEEE DOI 2002
Code, HDR. Dataset, HDR. Dataset, E2VID.
HTML Version. BibRef

Rebecq, H.[Henri], Gallego, G.[Guillermo], Mueggler, E.[Elias], Scaramuzza, D.[Davide],
EMVS: Event-Based Multi-View Stereo: 3D Reconstruction with an Event Camera in Real-Time,
IJCV(126), No. 12, December 2018, pp. 1394-1414.
Springer DOI 1811
BibRef

Zhou, Y.[Yi], Gallego, G.[Guillermo], Rebecq, H.[Henri], Kneip, L.[Laurent], Li, H.D.[Hong-Dong], Scaramuzza, D.[Davide],
Semi-dense 3D Reconstruction with a Stereo Event Camera,
ECCV18(I: 242-258).
Springer DOI 1810
BibRef


Tulyakov, S.[Stepan], Fleuret, F.[Francois], Kiefel, M.[Martin], Gehler, P.[Peter], Hirsch, M.[Michael],
Learning an Event Sequence Embedding for Dense Event-Based Deep Stereo,
ICCV19(1527-1537)
IEEE DOI 2004
Event camera. biomimetics, cameras, image representation, image sensors, learning (artificial intelligence), Power demand BibRef

Wang, Q.Y.[Qin-Yi], Zhang, Y.X.[Ye-Xin], Yuan, J.S.[Jun-Song], Lu, Y.L.[Yi-Long],
Space-Time Event Clouds for Gesture Recognition: From RGB Cameras to Event Cameras,
WACV19(1826-1835)
IEEE DOI 1904
Sense motion, event streams. space-time location of intensity change. cameras, gesture recognition, image motion analysis, image sensors, neural net architecture, individual event, space-time location, Real-time systems BibRef

Alzugaray, I., Chli, M.,
Asynchronous Multi-Hypothesis Tracking of Features with Event Cameras,
3DV19(269-278)
IEEE DOI 1911
BibRef
Earlier:
ACE: An Efficient Asynchronous Corner Tracker for Event Cameras,
3DV18(653-661)
IEEE DOI 1812
Tracking, Cameras, Feature extraction, Visualization, Streaming media, Robot vision systems, SLAM, dvs, visual odometry, visual tracking. image motion analysis, image sequences, efficient asynchronous corner tracker. BibRef

Pan, L.Y.[Li-Yuan], Scheerlinck, C.[Cedric], Yu, X.[Xin], Hartley, R.[Richard], Liu, M.M.[Miao-Miao], Dai, Y.[Yuchao],
Bringing a Blurry Frame Alive at High Frame-Rate With an Event Camera,
CVPR19(6813-6822).
IEEE DOI 2002
BibRef

Stoffregen, T.[Timo], Kleeman, L.[Lindsay],
Event Cameras, Contrast Maximization and Reward Functions: An Analysis,
CVPR19(12292-12300).
IEEE DOI 2002
Event cameras asynchronously report timestamped changes in pixel intensity. BibRef

Scheerlinck, C.[Cedric], Barnes, N.[Nick], Mahony, R.[Robert],
Continuous-Time Intensity Estimation Using Event Cameras,
ACCV18(V:308-324).
Springer DOI 1906
Asynchronous, data-driven measurements of local temporal contrast. BibRef

Gehrig, D.[Daniel], Loquercio, A.[Antonio], Derpanis, K.[Konstantinos], Scaramuzza, D.[Davide],
End-to-End Learning of Representations for Asynchronous Event-Based Data,
ICCV19(5632-5642)
IEEE DOI 2004
Event camers: pixel changes. cameras, computer vision, convolutional neural nets, image motion analysis, image representation, image sensors, Spatiotemporal phenomena BibRef

Gao, S., Guo, G., Chen, C.L.P.[C. L. Philip],
Event-Based Incremental Broad Learning System for Object Classification,
CEFRL19(2989-2998)
IEEE DOI 2004
cameras, convolutional neural nets, image classification, image sensors, learning (artificial intelligence), event camera BibRef

Gallego, G., Rebecq, H., Scaramuzza, D.,
A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation,
CVPR18(3867-3876)
IEEE DOI 1812
Trajectory, Estimation, Cameras, Optical imaging, Brightness, Image edge detection, Computer vision BibRef

Barua, S., Miyatani, Y., Veeraraghavan, A.,
Direct face detection and video reconstruction from event cameras,
WACV16(1-9)
IEEE DOI 1606
Cameras BibRef

Kim, H.[Hanme], Leutenegger, S.[Stefan], Davison, A.J.[Andrew J.],
Real-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera,
ECCV16(VI: 349-364).
Springer DOI 1611
BibRef

Kim, H.[Hanme], Handa, A.[Ankur], Benosman, R.[Ryad], Ieng, S.H.[Sio-Hoi], Davison, A.J.[Andrew J.],
Simultaneous Mosaicing and Tracking with an Event Camera,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Gobron, S.[Stéphane], Ahn, J.H.[Jung-Hyun], Garcia, D.[David], Silvestre, Q.[Quentin], Thalmann, D.[Daniel], Boulic, R.[Ronan],
An Event-Based Architecture to Manage Virtual Human Non-Verbal Communication in 3D Chatting Environment,
AMDO12(58-68).
Springer DOI 1208
BibRef

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Differencing Papers -- Ramesh Jain .


Last update:Aug 4, 2020 at 13:31:31