Extremely overlapping vehicle counting

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9117, Issue , 2015, Pages 423-431

  Guerrero Gómez, Ricardo Olmedo ^a   Torre Jiménez, Beatriz ^a   López Sastre, Roberto ^a   Maldonado Bascón, Saturnino ^a   Oñoro Rubio, Daniel ^a  

^a UNIVERSITY OF ALCALÁ   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

AMPHIBIOUS VEHICLES; IMAGE ANALYSIS; PATTERN RECOGNITION; VEHICLES;

EVALUATION METRICS; EXPERIMENTAL VALIDATIONS; MEAN ABSOLUTE ERROR; NUMBER OF VEHICLES; OBJECT COUNTING; SOURCE CODES; VEHICLE COUNTING;

TRAFFIC CONGESTION;

EID: 84937510504     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-19390-8_48     Document Type: Conference Paper

References (17)

1. Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The PASCAL visual object classes (VOC) challenge. IJCV 88(2), 303-338 (2010)
2. Guerrero-Gómez-Olmedo, R., López-Sastre, R.J., Maldonado-Bascón, S., Fernández-Caballero, A.: Vehicle tracking by simultaneous detection and viewpoint estimation. In: Ferrández Vicente, J.M., Álvarez Sánchez, J.R., de la Paz López, F., Toledo Moreo, F.J. (eds.) IWINAC 2013, Part II. LNCS, vol. 7931, pp. 306-316. Springer, Heidelberg (2013)
3. Geiger, A., Lenz, P., Stiller, C., Urtasun, R.: Vision meets robotics: the KITTI dataset. IJRR 32(11), 1231-1237 (2013)
4. Caraffi, C., Vojir, T., Trefny, J., Sochman, J., Matas, J.: A system for real-time detection and tracking of vehicles from a single car-mounted camera. In: ITS Conference (2012)
5. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: CVPR (2005)
6. Sudowe, P., Leibe, B.: Efficient use of geometric constraints for sliding-window object detection in video. In: Crowley, J.L., Draper, B.A., Thonnat, M. (eds.) ICVS 2011. LNCS, vol. 6962, pp. 11-20. Springer, Heidelberg (2011)
7. Lempitsky, V., Zisserman, A.: Learning to count objects in images. In: NIPS (2010)
8. Fiaschi, L., Köthe, U., Nair, R., Hamprecht, F.A.: Learning to count with regression forest and structured labels. In: ICPR (2012)
9. Chan, A.B., Liang, Z.S.J., Vasconcelos, N.: Privacy preserving crowd monitoring: counting people without people models or tracking. In: CVPR (2008)
10. Lu, W., Wang, S., Ding, X.: Vehicle detection and tracking in relatively crowded conditions. In: IEEE International Conference on Systems, Man, and Cybernetics (2009)
11. Jun, G., Aggarwal, J.K., Gökmen, M.: Tracking and segmentation of highway vehicles in cluttered and crowded scenes. In: IEEE Workshops on Applications of Computer Vision (2008)
12. Tamersoy, B., Aggarwal, J.K.: Robust vehicle detection for tracking in highway surveillance videos using unsupervised learning. In: AVSS (2009)
13. Chen, K., Loy, C.C., Gong, S., Xiang, T.: Feature mining for localised crowd counting. In: BMVC (2012)
14. Arteta, C., Lempitsky, V., Noble, J., Zisserman, A.: Learning to detect partially overlapping instances. In: CVPR (2013)
15. Selinummi, J., Seppala, J., Yli-Harja, O., Puhakka, J.A.: Software for quantification of labeled bacteria from digital microscope images by automated image analysis. Biotechniques 39(6), 859-863 (2005)
16. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2), 91-110 (2004)
17. Vedaldi, A., Fulkerson, B.: VLFeat: An open and portable library of computer vision algorithms (2008). http://www.vlfeat.org/