19.6.3.7.10 Birds, Detection, Identification

Chapter Contents (Back)
Bird Recognition.

Tao, Y., Chen, Z., Griffis, C.L.,
Chick feather pattern recognition,
VISP(151), No. 5, October 2004, pp. 337-344.
IEEE Abstract. 0501
BibRef

Song, D., Xu, Y.,
A Low False Negative Filter for Detecting Rare Bird Species From Short Video Segments Using a Probable Observation Data Set-Based EKF Method,
IP(19), No. 9, September 2010, pp. 2321-2331.
IEEE DOI 1008
BibRef

Huang, C.[Chao], Meng, F.[Fanman], Luo, W.[Wang], Zhu, S.[Shuyuan],
Bird breed classification and annotation using saliency based graphical model,
JVCIR(25), No. 6, 2014, pp. 1299-1307.
Elsevier DOI 1407
Graphical model BibRef

Gavves, E.[Efstratios], Fernando, B.[Basura], Snoek, C.G.M.[Cees G.M.], Smeulders, A.W.M.[Arnold W.M.], Tuytelaars, T.[Tinne],
Local Alignments for Fine-Grained Categorization,
IJCV(111), No. 2, January 2015, pp. 191-212.
Springer DOI 1502
BibRef
Earlier:
Fine-Grained Categorization by Alignments,
ICCV13(1713-1720)
IEEE DOI 1403
fine-grained categorization. Locate distinctive details by alignment to general models. Apply to birds and dogs. BibRef

Zhang, X.P.[Xiao-Peng], Xiong, H.K.[Hong-Kai], Zhou, W.G.[Wen-Gang], Tian, Q.[Qi],
Fused One-vs-All Features With Semantic Alignments for Fine-Grained Visual Categorization,
IP(25), No. 2, February 2016, pp. 878-892.
IEEE DOI 1601
Birds BibRef

Zhang, X.P.[Xiao-Peng], Xiong, H.K.[Hong-Kai], Zhou, W.G.[Wen-Gang], Lin, W.Y.[Wei-Yao], Tian, Q.[Qi],
Picking Neural Activations for Fine-Grained Recognition,
MultMed(19), No. 12, December 2017, pp. 2736-2750.
IEEE DOI 1712
BibRef
Earlier:
Picking Deep Filter Responses for Fine-Grained Image Recognition,
CVPR16(1134-1142)
IEEE DOI 1612
Automobiles, Birds, Detectors, Dogs, Neurons, Testing, Training, Fine-grained recognition, weakly supervised part discovery BibRef

Zhang, L., Yang, Y., Wang, M., Hong, R., Nie, L., Li, X.,
Detecting Densely Distributed Graph Patterns for Fine-Grained Image Categorization,
IP(25), No. 2, February 2016, pp. 553-565.
IEEE DOI 1601
Birds BibRef

Atanbori, J.[John], Duan, W.[Wenting], Murray, J.[John], Appiah, K.[Kofi], Dickinson, P.[Patrick],
Automatic classification of flying bird species using computer vision techniques,
PRL(81), No. 1, 2016, pp. 53-62.
Elsevier DOI 1609
Fine-grained classification BibRef

Scholz, N.[Nikolas], Moll, J.[Jochen], Mńlzer, M.[Moritz], Nagovitsyn, K.[Konstantin], Krozer, V.[Viktor],
Random bounce algorithm: Real-time image processing for the detection of bats and birds,
SIViP(10), No. 8, November 2016, pp. 1449-1456.
Springer DOI 1610
BibRef

Wei, X.S.[Xiu-Shen], Xie, C.W.[Chen-Wei], Wu, J.X.[Jian-Xin], Shen, C.H.[Chun-Hua],
Mask-CNN: Localizing parts and selecting descriptors for fine-grained bird species categorization,
PR(76), No. 1, 2018, pp. 704-714.
Elsevier DOI 1801
Fine-grained image recognition BibRef

Peng, Y.X.[Yu-Xin], He, X.T.[Xiang-Teng], Zhao, J.J.[Jun-Jie],
Object-Part Attention Model for Fine-Grained Image Classification,
IP(27), No. 3, March 2018, pp. 1487-1500.
IEEE DOI 1801
Automobiles, Birds, Feature extraction, Image classification, Noise measurement, Redundancy, Visualization, weakly supervised learning BibRef

Xiao, T.J.[Tian-Jun], Xu, Y.C.[Yi-Chong], Yang, K.Y.[Kui-Yuan], Zhang, J.X.[Jia-Xing], Peng, Y.X.[Yu-Xin], Zhang, Z.[Zheng],
The application of two-level attention models in deep convolutional neural network for fine-grained image classification,
CVPR15(842-850)
IEEE DOI 1510
BibRef

Zhao, J.J.[Jun-Jie], Peng, Y.X.[Yu-Xin],
Cost-Sensitive Deep Metric Learning for Fine-Grained Image Classification,
MMMod18(I:130-141).
Springer DOI 1802
BibRef


Serrano, S.A.[Sergio A.], BenÝtez-Jimenez, R.[Ricardo], Nu˝ez-Rosas, L.[Laura], del Coro Arizmendi, M.[Ma], Greeney, H.[Harold], Reyes-Meza, V.[Veronica], Morales, E.[Eduardo], Escalante, H.J.[Hugo Jair],
Automated Detection of Hummingbirds in Images: A Deep Learning Approach,
MCPR18(155-166).
Springer DOI 1807
BibRef

Coluccia, A., Ghenescu, M., Piatrik, T., De Cubber, G., Schumann, A., Sommer, L., Klatte, J., Schuchert, T., Beyerer, J., Farhadi, M., Amandi, R., Aker, C., Kalkan, S., Saqib, M., Sharma, N., Daud, S., Makkah, K., Blumenstein, M.,
Drone-vs-Bird detection challenge at IEEE AVSS2017,
AVSS17(1-6)
IEEE DOI 1806
military aircraft, terrorism, European Commission, Horizon 2020 program, IEEE AVSS2017, SafeShore project, Video sequences BibRef

Bender, M., Yang, X., Chen, H., Kurdila, A., MŘller, R.,
Gaussian process dynamic modeling of bat flapping flight,
ICIP17(4542-4546)
IEEE DOI 1803
Cameras, Data models, Dimensionality reduction, Kinematics, Manifolds, Mathematical model, Trajectory, Motion Capture BibRef

Pang, C., Li, H., Cherian, A., Yao, H.,
Part-based fine-grained bird image retrieval respecting species correlation,
ICIP17(2896-2900)
IEEE DOI 1803
Binary codes, Birds, Correlation, Image coding, Image recognition, Image retrieval, Task analysis, part detection BibRef

Srinivas, M., Lin, Y.Y., Liao, H.Y.M.,
Deep dictionary learning for fine-grained image classification,
ICIP17(835-839)
IEEE DOI 1803
Birds, Dictionaries, Feature extraction, Machine learning, Task analysis, Training, Training data, Sparse representation, on-line dictionary learning BibRef

Dash, A.[Amanda], Albu, A.B.[Alexandra Branzan],
Counting Large Flocks of Birds Using Videos Acquired with Hand-Held Devices,
ACIVS17(468-478).
Springer DOI 1712
BibRef

Elhoseiny, M., Zhu, Y., Zhang, H., Elgammal, A.,
Link the Head to the 'Beak': Zero Shot Learning from Noisy Text Description at Part Precision,
CVPR17(6288-6297)
IEEE DOI 1711
Birds, Head, Image recognition, Noise measurement, Training, Visualization BibRef

Wang, X., Zhao, Y.[Yue], Ji, Q.,
Taxonomy augmented object recognition,
ICPR16(1370-1375)
IEEE DOI 1705
Birds, Electronic mail, Measurement, Object recognition, Semantics, Support vector machines, Taxonomy BibRef

T'Jampens, R., Hernandez, F., Vandecasteele, F., Verstockt, S.,
Automatic detection, tracking and counting of birds in marine video content,
IPTA16(1-6)
IEEE DOI 1703
feature extraction BibRef

Wang, Q.S.[Qiao-Song], Rasmussen, C.[Christopher], Song, C.B.[Chun-Bo],
Fast, Deep Detection and Tracking of Birds and Nests,
ISVC16(I: 146-155).
Springer DOI 1701
BibRef

Huang, J.B., Caruana, R., Farnsworth, A., Kelling, S., Ahuja, N.,
Detecting Migrating Birds at Night,
CVPR16(2091-2099)
IEEE DOI 1612
BibRef

Mader, S., Grenzd÷rffer, G.J.,
Automatic Sea Bird Detection From High Resolution Aerial Imagery,
ISPRS16(B7: 299-303).
DOI Link 1610
BibRef

Huang, Y., Zheng, H., Yang, H.,
Improving an object tracker for infrared flying bird tracking,
ICIP16(1699-1703)
IEEE DOI 1610
Decision support systems BibRef

Takeki, A., Trinh, T.T., Yoshihashi, R., Kawakami, R., Iida, M., Naemura, T.,
Detection of small birds in large images by combining a deep detector with semantic segmentation,
ICIP16(3977-3981)
IEEE DOI 1610
Birds BibRef

Kemper, G., Weidauer, A., Coppack, T.,
Monitoring Seabirds And Marine Mammals By Georeferenced Aerial Photography,
ISPRS16(B8: 689-694).
DOI Link 1610
BibRef

Xie, L.X.[Ling-Xi], Wang, J.D.[Jing-Dong], Lin, W.Y.[Wei-Yao], Zhang, B.[Bo], Tian, Q.[Qi],
RIDE: Reversal Invariant Descriptor Enhancement,
ICCV15(100-108)
IEEE DOI 1602
Birds. Description to eliminate need for including reversals in descriptions. BibRef

Wilber, M.J., Kwak, I.S., Kriegman, D., Belongie, S.J.,
Learning Concept Embeddings with Combined Human-Machine Expertise,
ICCV15(981-989)
IEEE DOI 1602
Birds BibRef

Van Horn, G.[Grant], Branson, S.[Steve], Farrell, R.[Ryan], Haber, S.[Scott], Barry, J.[Jessie], Ipeirotis, P.[Panos], Perona, P.[Pietro], Belongie, S.J.[Serge J.],
Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection,
CVPR15(595-604)
IEEE DOI 1510
BibRef

Branson, S.[Steve], Van Horn, G.[Grant], Perona, P.[Pietro], Belongie, S.J.[Serge J.],
Improved Bird Species Recognition Using Pose Normalized Deep Convolutional Nets,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

J°rgensen, A.[Anders], Jensen, E.M.[Eigil M°lvig], Moeslund, T.B.[Thomas B.],
Detecting Gallbladders in Chicken Livers using Spectral Imaging Anders,
MVAB15(xx-yy).
DOI Link 1601
BibRef

Atanbori, J.[John], Duan, W.[Wenting], Murray, J.[John], Appiah, K.[Kofi], Dickinson, P.[Patrick],
A Computer Vision Approach to Classification of Birds in Flight from Video Sequences,
MVAB15(xx-yy).
DOI Link 1601
BibRef

Ge, Z.[Zong_Yuan], McCool, C.[Chris], Sanderson, C.[Conrad], Bewley, A.[Alex], Chen, Z.[Zetao], Corke, P.[Peter],
Fine-grained bird species recognition via hierarchical subset learning,
ICIP15(561-565)
IEEE DOI 1512
fine-grained classification; subset clustering BibRef

Yoshihashi, R.[Ryota], Kawakami, R.[Rei], Iida, M.[Makoto], Naemura, T.[Takeshi],
Construction of a bird image dataset for ecological investigations,
ICIP15(4248-4252)
IEEE DOI 1512
Image recognition BibRef

Tsukioka, H.[Hiroshi], Kudo, M.[Mineichi],
Selection of Features in Accord with Population Drift,
ICPR14(1591-1596)
IEEE DOI 1412
Birds BibRef

Borkar, T.S.[Tejas S.], Karam, L.J.[Lina J.],
Automated Bird Plumage Coloration Quantification in Digital Images,
ISVC14(II: 220-229).
Springer DOI 1501
BibRef

Goering, C.[Christoph], Rodner, E.[Erik], Freytag, A.[Alexander], Denzler, J.[Joachim],
Nonparametric Part Transfer for Fine-Grained Recognition,
CVPR14(2489-2496)
IEEE DOI 1409
bird classification BibRef

Berg, T.[Thomas], Liu, J.X.[Jiong-Xin], Lee, S.W.[Seung Woo], Alexander, M.L.[Michelle L.], Jacobs, D.W.[David W.], Belhumeur, P.N.[Peter N.],
Birdsnap: Large-Scale Fine-Grained Visual Categorization of Birds,
CVPR14(2019-2026)
IEEE DOI 1409
Fine-grained visual categorization BibRef

Angelova, A.[Anelia], Long, P.M.[Philip M.],
Benchmarking large-scale Fine-Grained Categorization,
WACV14(532-539)
IEEE DOI 1406
Birds BibRef

Angelova, A.[Anelia], Zhu, S.H.[Sheng-Huo],
Efficient Object Detection and Segmentation for Fine-Grained Recognition,
CVPR13(811-818)
IEEE DOI 1309
Laplacian propagation; fine-grained categorization; image segmentation. Low level regions into object. Use object for recognition. BibRef

Angelova, A.[Anelia], Niculescu-Mizil, A.[Alexandru],
Feature combination with Multi-Kernel Learning for fine-grained visual classification,
WACV14(241-246)
IEEE DOI 1406
Accuracy; Birds; Dictionaries; Dogs; Feature extraction; Kernel; Manuals BibRef

Berg, T.[Thomas], Belhumeur, P.N.[Peter N.],
How Do You Tell a Blackbird from a Crow?,
ICCV13(9-16)
IEEE DOI 1403
field guide; fine-grained recognition; visual similarity BibRef

Grenzd÷rffer, G.J.,
UAS-based automatic bird count of a common gull colony,
UAV-g13(169-174).
HTML Version. 1311
BibRef

Liu, J.X.[Jiong-Xin], Belhumeur, P.N.[Peter N.],
Bird Part Localization Using Exemplar-Based Models with Enforced Pose and Subcategory Consistency,
ICCV13(2520-2527)
IEEE DOI 1403
Fine-grained classification; Part localization See also Dog Breed Classification Using Part Localization. BibRef

Yao, B.P.[Bang-Peng], Bradski, G.R.[Gary R.], Fei-Fei, L.[Li],
A codebook-free and annotation-free approach for fine-grained image categorization,
CVPR12(3466-3473).
IEEE DOI 1208
Class is given, detailed classification. (e.g. birds) BibRef

Farrell, R.[Ryan], Oza, O.[Om], Zhang, N.[Ning], Morariu, V.I.[Vlad I.], Darrell, T.J.[Trevor J.], Davis, L.S.[Larry S.],
Birdlets: Subordinate categorization using volumetric primitives and pose-normalized appearance,
ICCV11(161-168).
IEEE DOI 1201
Differences between part-level characterizations, not just absence of parts. Bird identification. BibRef

Qing, C.M.[Chun-Mei], Dickinson, P.[Patrick], Lawson, S.[Shaun], Freeman, R.[Robin],
Automatic nesting seabird detection based on boosted HOG-LBP descriptors,
ICIP11(3577-3580).
IEEE DOI 1201
BibRef

Zhu, W.X.[Wei-Xing], Lu, C.F.[Chen-Fang], Li, X.C.[Xin-Cheng], Kong, L.W.[Ling-Wu],
Dead Birds Detection in Modern Chicken Farm Based on SVM,
CISP09(1-5).
IEEE DOI 0910
BibRef

Das, M.[Madirakshi], Manmatha, R.,
Automatic Segmentation and Indexing in a Database of Bird Images,
ICCV01(II: 351-358).
IEEE DOI 0106
Segmentation. BibRef

Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Agriculture, Inspection -- Fish, Fish Motion, Detection .


Last update:Aug 16, 2018 at 18:22:30