Source: http://www.google.ca/patents/US8484691
Timestamp: 2018-01-24 10:07:44
Document Index: 131746290

Matched Legal Cases: ['Application No. 02725522', 'Application No. 02752347', 'Application No. 02756525', 'Application No. 02782170', 'Application No. 04706547', 'Application No. 05778109']

Patent US8484691 - Copyright detection and protection system and method - Google Patents
A method for detecting against unauthorized transmission of digital works comprises the steps of maintaining a registry of information permitting identification of digital copyrighted works, monitoring a network for transmission of at least one packet-based digital signal, extracting at least one feature...http://www.google.ca/patents/US8484691?utm_source=gb-gplus-sharePatent US8484691 - Copyright detection and protection system and method
Publication number US8484691 B2
Also published as EP1490767A1, EP1490767A4, EP1490767B1, US7363278, US7565327, US7707088, US7711652, US7797249, US8645279, US8775317, US9589141, US20030037010, US20050154678, US20050154680, US20050154681, US20080141379, US20080154730, US20080155116, US20090077673, US20090328236, US20130276138, US20140115716, US20170169235, WO2002082271A1
Publication number 035599, 12035599, US 8484691 B2, US 8484691B2, US-B2-8484691, US8484691 B2, US8484691B2
Patent Citations (223), Non-Patent Citations (158), Referenced by (19), Classifications (33), Legal Events (3)
US 8484691 B2
1. A computer implemented method comprising: obtaining, through a network by a computer system, data pertaining to content transmitted during a data transmission transaction, creating, by the computer system, fingerprint from the transmitted content; sending, by the computer system, the data pertaining to the transmitted content to a copyright protection system, the data pertaining to the transmitted content representing the fingerprint of the transmitted content; receiving, from the copyright protection system, information indicating that at least a portion of the transmitted content matches at least a portion of one of a plurality of registered works, wherein the fingerprint is used to determine the match; sending the at least portion of the transmitted content and the at least portion of the one of the plurality of registered works that match the at least portion of the transmitted content to a recipient associated with the data transmission transaction; determining, by the computer system that the recipient contests blocking of the content being transmitted based on the at least portion of the transmitted content and the at least portion of the one of the plurality of registered works sent to the recipient; and sending a message to the copyright protection system to continue transmission of the content to the recipient.
2. The method of claim 1 wherein the transmitted content comprises one or more of audio, video, still images, games, or software.
3. The method of claim 1 wherein the transmitted content does not include information relevant to copyright violation detection.
4. The method of claim 1 wherein the data pertaining to the transmitted content represents at least a portion of a file comprising the transmitted content.
5. A website computer system comprising: memory; and at least one processor coupled to the memory to obtain data pertaining to content transmitted during a data transmission transaction; create a fingerprint from the transmitted content; send the data pertaining to the transmitted content to a copyright protection system, the data pertaining to the transmitted content representing the perceptual based fingerprint of the transmitted content; receive information indicating that at least a portion of the transmitted content matches at least a portion of one of a plurality of registered works, wherein the fingerprint is used to determine the match; send the at least portion of the transmitted content and the at least portion of the one of the plurality of registered works that match the at least portion of the transmitted content to a recipient associated with the data transmission transaction: determine that the recipient contests blocking of the content being transmitted based on the at least portion of the transmitted content and the at least portion of the one of the plurality of registered works sent to the recipient; and send a message to the copyright protection system to continue transmission of the content to the recipient.
6. The system of claim 5 wherein the transmitted content comprises one or more of audio, video, still images, games, or software.
7. The system of claim 5 wherein the transmitted content does not include information relevant to copyright violation detection.
8. The system of claim 5 wherein the data pertaining to the transmitted content represents at least a portion of a file comprising the transmitted content.
9. A non-transitory computer readable storage medium comprising instructions stored thereon that when executed by a computer cause the computer to perform a method comprising: obtaining data pertaining to content transmitted during a data transmission transaction; creating a fingerprint from the transmitted content; sending the data pertaining to the transmitted content to a copyright protection system, the data pertaining to the transmitted content representing the fingerprint of the transmitted content; receiving, from the copyright protection system, information indicating that at least a portion of the transmitted content matches at least a portion of one of a plurality of registered works, wherein the fingerprint is used to determine the match; sending the at least portion of the transmitted content and the at least portion of the one of the plurality of registered works that match the at least portion of the transmitted content to a recipient associated with the data transmission transaction; determining that the recipient contests blocking of the content being transmitted based on the at least portion of the transmitted content and the at least portion of the one of the plurality of registered works sent to the recipient; and sending a message to the copyright protection system to continue transmission of the content to the recipient.
10. The computer readable storage medium of claim 9 wherein the transmitted content comprises one or more of audio, video, still images, games, or software.
11. The computer readable storage medium of claim 9 wherein the transmitted content does not include information relevant to copyright violation detection.
12. The computer readable storage medium of claim 9 wherein the data pertaining to the transmitted content represents at least a portion of a file comprising the transmitted content.
The proposed algorithm considered here assumes that the sequence of features extracted from the song is statistically independent. Under this assumption, the likelihood of observing a feature vector {right arrow over (x)}t at time t is not dependent on the feature vector {right arrow over (x)}t-1 extracted at time t−1 or any other time for that matter. In other words, the likelihood of observing sequence of T feature vectors,
X = { x -> 1 , x -> 2 , … , x -> T }
p ( X ❘ λ ) = ∏ t = 1 T p ( x -> t ❘ λ ) ( Eqn . 7 )
log p ( X ❘ λ ) = ∑ t = 1 T log p ( x -> t ❘ λ ) ( Eqn . 8 )
X = { x -> 1 , x -> 2 , … , x -> T } ,
p ( x -> ❘ λ ) = ∑ m = 1 M w m · b m ( x -> ) ( Eqn . 10 )
b m ( x -> ) = 1 ( 2 π ) D / 2  ∑ m  1 / 2 exp { - 1 2 ( x -> - μ -> m ) ′ ∑ m - 1 ( x -> - μ -> m ) } ( Eqn . 11 )
X = { x → 1 , x → 2 , … , x → T } .
The M covariance vectors are initialized to have unit variance for each feature element and mixture weights are initialized to have equal weighting (i.e., wm=1/M).
µ _ → m = ∑ t = 1 T p ( m | x → r , λ ) · x → t ∑ t = 1 T p ( m | x → t , λ ) ( Eqn . 16 )
σ _ m 2 = ∑ t = 1 T p ( m | x → t , λ ) · x → t 2 ∑ t = 1 T p ( m | x → t , λ ) - µ _ → m 2 ( Eqn . 17 )
log p ( x → | λ ) = log { ∑ m = 1 M w m ( 2 π ) D / 2  ∑ m  1 / 2 exp { - 1 2 ( x → - µ → m ) ′ ∑ m - 1 ( x → - µ → m ) } } ( Eqn . 19 )
log p ( x → | λ ) = log { ∑ m = 1 M w m ( 2 π ) D / 2 ∏ j = 1 D σ m 2 [ j ] exp { - 1 2 ∑ j = 1 D ( x t [ j ] - µ m [ j ] ) 2 σ m 2 [ j ] } } ( Eqn . 20 )
log p ( x → | λ ) ≈ arg max 1 ≤ m ≤ M { C m - 1 2 ∑ j = 1 D ( x t [ j ] - µ m [ j ] ) 2 σ m 2 [ j ] } ( Eqn . 21 )
X = { x → 1 , x → 2 , … , x → T } ,
US6490279 * 23 Jul 1998 3 Dec 2002 Advanced Communication Device, Inc. Fast data base research and learning apparatus
1 "How does PacketHound work?", www.palisdesys.com/products/packethound/how-does-it-work/prod-Pghow.shtml 2002.
2 "How does PacketHound work?", www.palisdesys.com/products/packethound/how—does—it—work/prod—Pghow.shtml 2002.
4 Audible Magic Magic Notice of Allowance for U.S. Appl. No. 12/042,023 mailed Jun. 25, 2009.
14 Audible Magic Notice of Allowance for U.S. Appl. No. 11/116,710 mailed Nov. 19. 2007.
23 Audible Magic Office Action for 09/511,632 mailed Aug. 27, 2003.
56 Audible Magic Office Action for U.S. Appl. No. 10/072,238 mailed Apr. 25, 2006.
57 Audible Magic Office Action for U.S. Appl. No. 10/072,238 mailed Apr. 7, 2008.
58 Audible Magic Office Action for U.S. Appl. No. 10/072,238 mailed Aug. 6, 2010.
59 Audible Magic Office Action for U.S. Appl. No. 10/072,238 mailed Jan. 9, 2009.
60 Audible Magic Office Action for U.S. Appl. No. 10/072,238 mailed Mar. 31, 2009.
61 Audible Magic Office Action for U.S. Appl. No. 10/072,238 mailed May 3, 2005.
62 Audible Magic Office Action for U.S. Appl. No. 10/072,238 mailed Oct. 1, 2008.
63 Audible Magic Office Action for U.S. Appl. No. 10/072,238 mailed Oct. 25, 2005.
64 Audible Magic Office Action for U.S. Appl. No. 10/072,238 mailed Sep. 19, 2007.
65 Audible Magic Office Action for U.S. Appl. No. 10/192,783 mailed Dec. 13, 2004.
66 Audible Magic Office Action for U.S. Appl. No. 10/356,318 mailed Apr. 11, 2007.
67 Audible Magic Office Action for U.S. Appl. No. 10/356,318 mailed Jan. 21, 2010.
68 Audible Magic Office Action for U.S. Appl. No. 10/356,318 mailed Jan. 6, 2009.
69 Audible Magic Office Action for U.S. Appl. No. 10/356,318 mailed May 24, 2006.
70 Audible Magic Office Action for U.S. Appl. No. 10/356,318 mailed May 9, 2008.
71 Audible Magic Office Action for U.S. Appl. No. 10/356,318 mailed Nov. 1, 2007.
72 Audible Magic Office Action for U.S. Appl. No. 10/356,318 mailed Nov. 2, 2006.
73 Audible Magic Office Action for U.S. Appl. No. 11/048,307 mailed Aug. 22, 2007.
74 Audible Magic Office Action for U.S. Appl. No. 11/048,307 mailed May 16, 2008.
75 Audible Magic Office Action for U.S. Appl. No. 11/048,308 mailed Feb. 25, 2008.
76 Audible Magic Office Action for U.S. Appl. No. 11/048,308 mailed Mar. 5, 2009.
77 Audible Magic Office Action for U.S. Appl. No. 11/048,338 mailed Apr. 18, 2007.
78 Audible Magic Office Action for U.S. Appl. No. 11/048,338 mailed Dec. 28, 2009.
79 Audible Magic Office Action for U.S. Appl. No. 11/048,338 mailed Jan. 14, 2008.
80 Audible Magic Office Action for U.S. Appl. No. 11/048,338 mailed Jan. 7, 2009.
81 Audible Magic Office Action for U.S. Appl. No. 11/048,338 mailed Jul. 6, 2009.
82 Audible Magic Office Action for U.S. Appl. No. 11/048,338 mailed Jul. 9, 2008.
83 Audible Magic Office Action for U.S. Appl. No. 11/048,338 mailed Jun. 24, 2010.
84 Audible Magic Office Action for U.S. Appl. No. 11/048,338 mailed Oct. 11, 2007.
85 Audible Magic Office Action for U.S. Appl. No. 11/116,710 mailed Apr. 20, 2006.
86 Audible Magic Office Action for U.S. Appl. No. 11/116,710 mailed Apr. 8, 2005.
87 Audible Magic Office Action for U.S. Appl. No. 11/116,710 mailed Dec. 13, 2004.
88 Audible Magic Office Action for U.S. Appl. No. 11/116,710 mailed Jan. 16, 2007.
89 Audible Magic Office Action for U.S. Appl. No. 11/116,710 mailed Jul. 31, 2006.
90 Audible Magic Office Action for U.S. Appl. No. 11/116,710 mailed Oct. 7, 2005.
91 Audible Magic Office Action for U.S. Appl. No. 11/191,493 mailed Apr. 28, 2009.
92 Audible Magic Office Action for U.S. Appl. No. 11/191,493 mailed Jan. 9, 2009.
93 Audible Magic Office Action for U.S. Appl. No. 11/191,493 mailed Jul. 17, 2008.
94 Audible Magic Office Action for U.S. Appl. No. 11/191,493 mailed Nov. 19, 2009.
95 Audible Magic Office Action for U.S. Appl. No. 11/239,543 mailed Apr. 23, 2008.
96 Audible Magic Office Action for U.S. Appl. No. 12/035,609 mailed Dec. 29, 2008.
97 Audible Magic Office Action for U.S. Appl. No. 12/035,609 mailed Jun. 24, 2009.
98 Audible Maigc Office Action for U.S. Appl. No. 10/356,318 mailed Jun. 15, 2009.
99 Audible Matic Office Action for U.S. Appl. No. 09/910,680 mailed Aug. 8, 2006.
100 Baum, L., et al., "A Maximization Technique Occurring in the Statistical Analysis of Probabilstic Functions of Markov Chains," The Annals of Mathematical Statisics, vol. 41, No. 1, pp. 164-171, 1970.
101 Beritelli, F., et al., "Multilayer Chaotic Encryption for Secure Communications in packet switching Networks," IEEE, vol. 2Aug. 2000, pp. 1575-1582.
102 Blum, T., Keislar, D., Wheaton, J., and Wold, E., "Audio Databases with Content-Based Retrieval," Prodeedings of the 1995 International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Intelligent Multimedia Information Retrieval, 1995.
103 Breslin, Pat, et al., Relatable Website, "Emusic uses Relatable's open source audio recongnition solution, TRM, to signature its music catabblog for MusicBrainz database," http://www.relatable.com/news/pressrelease/001017.release.html, Oct. 17, 2000.
104 Business Wire, "Cisco and Fox Host Groundbreaking Screening of Titan A.E.; Animated Epic Will Be First Film Ever to be Digitaly Transmitted Over the Internet Monday," Jun. 5, 2000, 08:14 EDT.
105 Business Wire, "IBM: IBM Announces New Descrambler Software; First to Offer Software to Work With Digital Video Chips," Jun. 5, 25, 1997, 07:49.
106 * Combatting Software Piracy by encryption and key management by Douglas Albert et al.; 1984; 6 pages.
107 Cosi, P., De Poli, G., Prandoni, P., "Timbre Characterization with Mel-Cepstrum and Neural Nets," Proceedings of the 1994 International Computer Music Conference, pp. 42-45, San Francisco, No date.
108 Dempster, A.P., et al., "Maximum Likelihood from Incomplete Data via the EM Algorithm" Journal of the Royal Statistical Society, Series B (Methodological), vol. 39, Issue 1, pp. 31-38, 1977.
109 European Patent Application No. 02725522.3, Supplementary European Search Report Dated May 12, 2006, 2 Pages.
110 European Patent Application No. 02752347.1, Supplementary European Search Report Dated May 8, 2006, 4 pages.
111 European Patent Application No. 02756525.8, Supplementary European Search Report Dated Jun. 28, 2006, 4 pages.
112 European Patent Application No. 02782170, Supplementary European Search Report Dated Feb. 7, 2007, 4 pages.
113 European Patent Application No. 04706547.9 European Search Report dated Feb. 25, 2010, 3 pages.
114 European Patent Application No. 05778109.8 European Search Report Dated Sep. 10, 2010, 7 Pages.
115 Feiten, B. and Gunzel, S., "Automatic Indexing of a Sound Database Using Self-Organizing Neural Nets," Computer Music Journal, 18:3, pp. 53-65, Fall 1994.
116 Fischer, S., Lienhart, R., and Effelsberg, W., "Automatic Recognition of Film Genres," Reihe Informatik, Jun. 1995, Universitat Mannheim, Praktische Informatik IV, L15, 16, D-68131 Mannheim.
117 Foote, J., "A Similarity Measure for Automatic Audio Classification," Institute of Systems Science, National University of Singapore, 1977, Singapore.
118 Gasaway Laura, Close of Century Sees New Copyright Amendments, Mar. 200, Information Outlook, 4, 3, 42.
119 Gonzalez, R. and Melih, K., "Content Based Retrieval of Audio," The Institute for Telecommunication Research, University of Wollongong, Australia, No date.
120 Haitsma, J., et al., "Robust Audio Hashing for Content Identification", CBMI 2001, Second International Workshop on Content Based Multimedia and Indexing, Brescia, Italy, Sep. 19-21, 2001.
121 Harris, Lesley Ellen, "To register or not," Mar. 2006, Information Outlook, 10, 3, 32(s).
122 Kanth, K.V. et al. "Dimensionality Reduction or Similarity Searching in Databases," Computer Vision and Image understanding, vol. 75, Nos. 1/2 Jul./Aug. 1999, pp. 59-72, Academic Press. Santa Barbara, CA, USA.
123 Keislar, D., Blum, T., Wheaton, J., and Wold, E., "Audio Analysis for Content-Based Retrieval" Proceedings of the 1995 International Computer Music Conference.
124 Ohtsuki, K., et al. , "Topic extraction based on continuos speech recognition in broadcast-news speech," Proceedings IEEE Workshop on Automated Speech Recognition and Understanding, 1997, pp. 527-534, N.Y., N.Y., USA.
125 Packethound Tech Specs, www.palisdesys.com/products/packethount/tck specs/prodPhtechspecs.shtml, 2002.
126 Pankanti, Sharath, "Verification Watermarks on Fingerprint Recognition and Retrieval," Part of IS&T/SPIE Conference on Security and Watermarking of Multimedia Contents, San Jose, CA Jan. 1999, SPIE vol. 3657, pp. 66-78.
127 PCT Search Report PCT/US01/50295, International Search Report dated May 14, 2003, 5 Pages.
128 PCT Search Report PCT/US02/10615, International Search Report dated Aug. 7, 2002, 2 Pages.
129 PCT Search Report PCT/US02/33186, International Search Report dated Dec. 16, 2002, pp. 1-4.
130 PCT Search Report PCT/US05/26887, International Search Report dated May 3, 2006, 2 Pages.
131 PCT Search Report PCT/US08/09127, International Search Report dated Oct. 30, 2008, 8 Pages.
132 PCT Search Report PCT/USO4/02748, International Search Report and Written Opinion dated Aug. 20, 2007, 6 Pages.
133 Pellom, B. et al., "Fast Likelihood Computation Techniques in Nearest-Neighbor search for Continuous Speech Recognition.", IEEE Signal Processing Letters, vol. 8, pp. 221-224 Aug. 2001.
134 Reynolds, D., et al., "Robust Text-Independent Speaker Identification Using Gaussian Mixture Speaker Models", IEEE Transactions on Speech and Audio Procsessing, vol. 3, No. 1, pp. 72-83.
135 Scheirer, E.D., "Tempo and Beat Analysis of Acoustic Musical Signals," Machine Listening Group, E15-401D MIT Media Laboratory, pp. 1-21, Aug. 8, 1997, Cambridge, MA.
136 Schneier, Bruce, Applied Cryptography, Protocols, Algorithms and Source Code in C, Chapter 2 Protocol Building Blocks, 1996, pp. 30-31.
137 Sheirer. E,, Slaney, M., "Construction and Evaluation of a Robust Multifeature Speech/Music Discriminator," pp, 1-4, Proceedings of ICASSP-97, Apr. 2-24, Munich, Germany.
138 Smith, Alan J., "Cache Memories," Computer Surveys, Sep. 1982, University of California, Berkeley, California, vol. 14, No. 3, pp. 1-61.
139 USPTO Notice of Allowance for U.S. Appl. No. 09/999,763 mailed Sep. 16, 2010.
140 USPTO Notice of Allowance for U.S. Appl. No. 11/923,491 mailed Sep. 29, 2011.
141 USPTO Notice of Allowance for U.S. Appl. No. 12/405,174 mailed Jan. 4, 2012.
142 USPTO Notice of Allowance for U.S. Appl. No. 12/410,445 mailed Aug. 12, 2011.
143 USPTO Notice of Allowance for U.S. Appl. No. 12/410,445 mailed Oct. 20, 2010.
144 USPTO Notice of Allowance forU.S. Appl. No. 12/482,313 mailed Aug. 23, 2011.
145 USPTO Office Action for U.S. Appl. No. 10/356,318 mailed Jan. 7, 2011.
146 USPTO Office Action for U.S. Appl. No. 11/191,493 mailed Oct. 4, 2010.
147 USPTO Office Action for U.S. Appl. No. 11/829,662 mailed Oct. 8, 2010.
148 USPTO Office Action for U.S. Appl. No. 11/923,491 mailed Nov. 12, 2010.
149 USPTO Office Action for U.S. Appl. No. 12/405,174 mailed Mar. 2, 2011.
150 USPTO Office Action for U.S. Appl. No. 12/405,174 mailed Sep. 9, 2011.
151 USPTO Office Action for U.S. Appl. No. 12/410,445 mailed Aug. 10, 2010.
152 USPTO Office Action for U.S. Appl. No. 12/488,504 mailed Nov. 10, 2010.
153 USPTO Office Action forU.S. Appl. No. 12/482,313 mailed Feb. 4, 2011.
157 Yong-Cong Chen, et al, A Secure and Robust Digital Watermaking Technique by the Blcok Cipher RC6 and Secure Hash Algorithm, Deparment of Computer Science, National Tsing Hua University, 2001.
158 Zawodny, Jeremy, D., "A C Program to Compute CDDB discids on Linus and FreeBSD," [Internet] http://jeremy.zawodny.com/c/discid-linux-1.3tar.gz, 1 page, Apr. 14, 2001, retrieved Jul. 17, 2007.
US8856104 * 16 Jun 2009 7 Oct 2014 Oracle International Corporation Querying by concept classifications in an electronic data record system
US8930386 16 Jun 2009 6 Jan 2015 Oracle International Corporation Querying by semantically equivalent concepts in an electronic data record system
US9087501 13 Mar 2014 21 Jul 2015 Yamaha Corporation Sound signal analysis apparatus, sound signal analysis method and sound signal analysis program
US9171532 * 14 Mar 2014 27 Oct 2015 Yamaha Corporation Sound signal analysis apparatus, sound signal analysis method and sound signal analysis program
US9854057 6 May 2014 26 Dec 2017 International Business Machines Corporation Network data collection and response system
US20100318548 * 16 Jun 2009 16 Dec 2010 Florian Alexander Mayr Querying by Concept Classifications in an Electronic Data Record System
US20140260912 * 14 Mar 2014 18 Sep 2014 Yamaha Corporation Sound signal analysis apparatus, sound signal analysis method and sound signal analysis program
U.S. Classification 725/116, 705/65
International Classification G06Q50/18, G06Q30/02, G06Q40/00, G06Q30/06, G06Q20/36, H04L29/06, H04N7/173, G06Q20/38, G06F21/00
Cooperative Classification G06F21/6209, G06F21/60, H04L63/1408, H04L63/104, H04L63/04, G06Q50/184, G06Q50/18, G06Q40/00, G06Q30/0255, G06Q20/3674, G06F2221/074, G06F2221/0737, G06F17/30743, G06F17/30047, G06F17/30026, H04L2463/101, H04L63/12, G06Q30/0601, G06Q20/383, H04L2463/103, H04L2463/102, G06F21/10