kbibtex-testset/bib/mendeley1.bib

0001 Automatically generated by Mendeley 1.3
0002 Any changes to this file will be lost if it is regenerated by Mendeley.
0003
0004 @article{VandeSande2010,
0005 abstract = {Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been proposed. Because many different descriptors exist, a structured overview is required of color invariant descriptors in the context of image category recognition. Therefore, this paper studies the invariance properties and the distinctiveness of color descriptors (software to compute the color descriptors from this paper is available from http://www.colordescriptors.com) in a structured way. The analytical invariance properties of color descriptors are explored, using a taxonomy based on invariance properties with respect to photometric transformations, and tested experimentally using a data set with known illumination conditions. In addition, the distinctiveness of color descriptors is assessed experimentally using two benchmarks, one from the image domain and one from the video domain. From the theoretical and experimental results, it can be derived that invariance to light intensity changes and light color changes affects category recognition. The results further reveal that, for light intensity shifts, the usefulness of invariance is category-specific. Overall, when choosing a single descriptor and no prior knowledge about the data set and object and scene categories is available, the OpponentSIFT is recommended. Furthermore, a combined set of color descriptors outperforms intensity-based SIFT and improves category recognition by 8 percent on the PASCAL VOC 2007 and by 7 percent on the Mediamill Challenge.},
0006 author = {van de Sande, Koen and Gevers, Theo and Snoek, Cees},
0007 doi = {10.1109/TPAMI.2009.154},
0008 file = {:C$\backslash$:/Users/BarisEvrim/Documents/Mendeley Desktop/GeversPAMI10.pdf:pdf},
0009 issn = {1939-3539},
0010 journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
0011 keywords = {Algorithms,Artificial Intelligence,Color,Colorimetry,Colorimetry: methods,Image Enhancement,Image Enhancement: methods,Image Interpretation, Computer-Assisted,Image Interpretation, Computer-Assisted: methods,Imaging, Three-Dimensional,Imaging, Three-Dimensional: methods,Pattern Recognition, Automated,Pattern Recognition, Automated: methods,Reproducibility of Results,Sensitivity and Specificity},
0012 month = sep,
0013 number = {9},
0014 pages = {1582--96},
0015 pmid = {20634554},
0016 title = {{Evaluating color descriptors for object and scene recognition.}},
0017 url = {http://www.ncbi.nlm.nih.gov/pubmed/20634554},
0018 volume = {32},
0019 year = {2010}
0020 }
0021 @inproceedings{KaewTraKulPong2001,
0022 author = {KaewTraKulPong, P. and Bowden, R},
0023 booktitle = {Proc. 2nd European Workshop on Advanced Video Based Surveillance Systems},
0024 file = {:C$\backslash$:/Users/BarisEvrim/Documents/Mendeley Desktop/KaewTraKulPong-AVBS01.pdf:pdf},
0025 pages = {1--5},
0026 title = {{An improved adaptive background mixture model for real-time tracking with shadow detection}},
0027 volume = {25},
0028 year = {2001}
0029 }
0030 @inproceedings{VandeSande2008,
0031 author = {van de Sande, K. and Gevers, T. and Snoek, C.G.M.},
0032 booktitle = {European Conference on Color in Graphics, Imaging and Vision},
0033 file = {:C$\backslash$:/Users/BarisEvrim/Documents/Mendeley Desktop/vandesande-cgiv2008.pdf:pdf},
0034 number = {2},
0035 pages = {378--381},
0036 title = {{Color descriptors for object category recognition}},
0037 volume = {2},
0038 year = {2008}
0039 }
0040 @article{Rosten2006a,
0041 author = {Rosten, E. and Drummond, T.},
0042 file = {:C$\backslash$:/Users/BarisEvrim/Documents/Mendeley Desktop/10.1.1.60.3991.pdf:pdf},
0043 journal = {Proc. ECCV},
0044 pages = {430--443},
0045 publisher = {Springer},
0046 title = {{Machine learning for high-speed corner detection}},
0047 year = {2006}
0048 }
0049 @article{Bernardin2008a,
0050 author = {Bernardin, Keni and Stiefelhagen, Rainer},
0051 doi = {10.1155/2008/246309},
0052 file = {:C$\backslash$:/Users/BarisEvrim/Documents/Mendeley Desktop/246309.pdf:pdf},
0053 issn = {1687-5176},
0054 journal = {EURASIP Journal on Image and Video Processing},
0055 pages = {1--10},
0056 title = {{Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics}},
0057 volume = {2008},
0058 year = {2008}
0059 }
0060 @article{Vondrick2010,
0061 author = {Vondrick, C. and Ramanan, D. and Patterson, D.},
0062 file = {:C$\backslash$:/Users/BarisEvrim/Documents/Mendeley Desktop/scalingup.pdf:pdf},
0063 journal = {Proc. ECCV},
0064 pages = {610--623},
0065 publisher = {Springer},
0066 title = {{Efficiently Scaling Up Video Annotation with Crowdsourced Marketplaces}},
0067 year = {2010}
0068 }
0069 @article{Calonder2010a,
0070 author = {Calonder, M. and Lepetit, V. and Strecha, C. and Fua, P.},
0071 file = {:C$\backslash$:/Users/BarisEvrim/Documents/Mendeley Desktop/10.1.1.175.2122.pdf:pdf},
0072 journal = {Proc. ECCV},
0073 pages = {778--792},
0074 publisher = {Springer},
0075 title = {{Brief: Binary robust independent elementary features}},
0076 year = {2010}
0077 }
0078 @article{Zivkovic2006a,
0079 author = {Zivkovic, Z. and van der Heijden, F.},
0080 doi = {10.1016/j.patrec.2005.11.005},
0081 file = {:C$\backslash$:/Users/BarisEvrim/Documents/Mendeley Desktop/zivkovicPRL2006.pdf:pdf},
0082 issn = {01678655},
0083 journal = {Pattern Recognition Letters},
0084 keywords = {background subtraction,gaussian mixture model,non-parametric density estimation,on-line density estimation},
0085 month = may,
0086 number = {7},
0087 pages = {773--780},
0088 title = {{Efficient adaptive density estimation per image pixel for the task of background subtraction}},
0089 volume = {27},
0090 year = {2006}
0091 }
0092 @article{Everingham2009,
0093 author = {Everingham, Mark and Gool, Luc and Williams, Christopher K. I. and Winn, John and Zisserman, Andrew},
0094 doi = {10.1007/s11263-009-0275-4},
0095 file = {:C$\backslash$:/Users/BarisEvrim/Documents/Mendeley Desktop/everingham10.pdf:pdf},
0096 issn = {0920-5691},
0097 journal = {International Journal of Computer Vision},
0098 keywords = {benchmark,database,object recognition},
0099 month = sep,
0100 number = {2},
0101 pages = {303--338},
0102 title = {{The Pascal Visual Object Classes (VOC) Challenge}},
0103 volume = {88},
0104 year = {2009}
0105 }