CAN CSA-ISO IEC TR 15938-8A-2005 Information technology - Multimedia content description interface - Part 8 Extraction and use of MPEG-7 descriptions AMENDMENT 1 Extensions of extr.pdf

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1、 Reference numberISO/IEC TR 15938-8:2002/Amd.1:2004(E)ISO/IEC 2004Information technology Multimedia content description interface Part 8: Extraction and use of MPEG-7 descriptions AMENDMENT 1: Extensions of extraction and use of MPEG-7 descriptions Technologies de linformation Interface de descripti

2、on du contenu multimdia Partie 8: Extraction et utilisation des descriptions MPEG-7 AMENDEMENT 1: Extensions dextraction et utilisation des descriptions MPEG-7 Amendment 1:2005 toNational Standard of CanadaCAN/CSA-ISO/IEC TR 15938-8:04Amendment 1:2004 to International Standard ISO/IEC TR 15938-8:200

3、2 has been adopted withoutmodification (IDT) as Amendment 1:2005 to CAN/CSA-ISO/IEC TR 15938-8:04. This Amendment wasreviewed by the CSA Technical Committee on Information Technology (TCIT) under the jurisdiction of theStrategic Steering Committee on Information Technology and deemed acceptable for

4、use in Canada.October 2005ISO/IEC TR 15938-8:2002/Amd.1:2004(E) PDF disclaimer This PDF file may contain embedded typefaces. In accordance with Adobes licensing policy, this file may be printed or viewed but shall not be edited unless the typefaces which are embedded are licensed to and installed on

5、 the computer performing the editing. In downloading this file, parties accept therein the responsibility of not infringing Adobes licensing policy. The ISO Central Secretariat accepts no liability in this area. Adobe is a trademark of Adobe Systems Incorporated. Details of the software products use

6、d to create this PDF file can be found in the General Info relative to the file; the PDF-creation parameters were optimized for printing. Every care has been taken to ensure that the file is suitable for use by ISO member bodies. In the unlikely event that a problem relating to it is found, please i

7、nform the Central Secretariat at the address given below. ISO/IEC 2004 All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and microfilm, without permission in writing

8、 from either ISO at the address below or ISOs member body in the country of the requester. ISO copyright office Case postale 56 CH-1211 Geneva 20 Tel. + 41 22 749 01 11 Fax + 41 22 749 09 47 E-mail copyrightiso.org Web www.iso.org ii ISO/IEC 2004 All rights reservedISO/IEC TR 15938-8:2002/Amd.1:2004

9、(E) ISO/IEC 2004 All rights reserved iiiForeword ISO (the International Organization for Standardization) and IEC (the International Electrotechnical Commission) form the specialized system for worldwide standardization. National bodies that are members of ISO or IEC participate in the development o

10、f International Standards through technical committees established by the respective organization to deal with particular fields of technical activity. ISO and IEC technical committees collaborate in fields of mutual interest. Other international organizations, governmental and non-governmental, in

11、liaison with ISO and IEC, also take part in the work. In the field of information technology, ISO and IEC have established a joint technical committee, ISO/IEC JTC 1. International Standards are drafted in accordance with the rules given in the ISO/IEC Directives, Part 2. The main task of the joint

12、technical committee is to prepare International Standards. Draft International Standards adopted by the joint technical committee are circulated to national bodies for voting. Publication as an International Standard requires approval by at least 75 % of the national bodies casting a vote. In except

13、ional circumstances, the joint technical committee may propose the publication of a Technical Report of one of the following types: type 1, when the required support cannot be obtained for the publication of an International Standard, despite repeated efforts; type 2, when the subject is still under

14、 technical development or where for any other reason there is the future but not immediate possibility of an agreement on an International Standard; type 3, when the joint technical committee has collected data of a different kind from that which is normally published as an International Standard (“

15、state of the art”, for example). Technical Reports of types 1 and 2 are subject to review within three years of publication, to decide whether they can be transformed into International Standards. Technical Reports of type 3 do not necessarily have to be reviewed until the data they provide are cons

16、idered to be no longer valid or useful. Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent rights. Amendment 1 to ISO/IEC TR 15938-8:2002 was prepared b

17、y Joint Technical Committee ISO/IEC JTC 1, Information technology, Subcommittee SC 29, Coding of audio, picture, multimedia and hypermedia information. NOTE This document preserves the sectioning of ISO/IEC TR 15938-8:2002. The text and figures given in this document are currently being considered a

18、s additions and/or modifications to those corresponding sections in ISO/IEC TR 15938-8:2002. ISO/IEC TR 15938-8:2002/Amd.1:2004(E) ISO/IEC 2004 All rights reserved 1Information technology Multimedia content description interface Part 8: Extraction and use of MPEG-7 descriptions AMENDMENT 1: Extensio

19、ns of extraction and use of MPEG-7 descriptions Add after subclause 5.6: 5.7 GofGopFeature This datatype is used to describe a certain visual feature representative of a series of video frames or collection of pictures. It is obtained by aggregating the visual descriptors extracted from each video f

20、rame or image in the collection. 5.7.1 Feature Extraction First, the extraction algorithm computes a descriptor of the visual feature for each frame in the sequence or each image in the collection. The extraction is specified in the subclauses corresponding to the descriptor used (e.g. for Homogeneo

21、usTexture, subclause 4.3.1.1 is used). Once the values of the frame/image-based descriptors are computed, a instance of GofGopFeature is derived by the aggregation procedure corresponding to the descriptor used; as defined in ISO/IEC 15938-3. There are three aggregation methods (i.e. Average, Median

22、, SplitMerge) as follows: null Average: Each component of descriptors in the GOF or GOP is summed and then averaged to compose the aggregated description null Median: Each component of descriptors in the GOF or GOP is sorted and then the middle value is selected to compose the aggregated description

23、. null SplitMerge: The DominantColor descriptors from different images are aggregated by merging of the clusters (“Value” elements) of different descriptors based on their proximity in colour space (the clusters within the same descriptor are also included as a special case, although if the extracti

24、on algorithm from 4.2.3.1 is followed, their distance will be greater than DISTANCE_MIN specified below). The merging procedure is performed iteratively, starting with the closest pair and repeating until only a small number of combined clusters remains. The outline of this algorithm is as follows:

25、closest_distance=0 ISO/IEC TR 15938-8:2002/Amd.1:2004(E) 2 ISO/IEC 2004 All rights reservedWhile (number_of_clusters MAX_NUM_OF_CLUSTERS or closest_distance 48 34 32 12 10 13 9 10 14 15 16 12 ISO/IEC TR 15938-8:2002/Amd.1:2004(E) ISO/IEC 2004 All rights reserved 3In the second example, “Average” is

26、used to aggregate descriptions. 48 34 32 15 11 13 9 8 14 15 16 12 In the following example, an instance of DominantColor is embedded in the GofGopFeature datatype. 0 5 0 89 203 0 1 1 14 120 43 74 0 1 0 12 243 212 27 1 0 0 In the following two examples, an instance of EdgeHistogram is embedded in the

27、 GofGopFeature datatype. In the first example, there is no specification of aggregation method 2 6 4 4 2 1 7 5 3 2 1 6 4 2 2 2 5 4 5 3 1 5 5 6 5 2 6 5 4 4 1 6 4 4 4 0 6 3 5 2 1 5 5 6 6 4 2 3 6 7 3 2 5 5 7 3 2 4 4 7 1 5 6 4 6 1 5 7 4 5 1 6 4 6 5 1 3 4 7 6 In the second example, “Average” is used to a

28、ggregate descriptions. ISO/IEC TR 15938-8:2002/Amd.1:2004(E) 4 ISO/IEC 2004 All rights reserved2 6 4 4 2 1 7 5 3 2 1 6 4 2 2 2 5 4 5 3 1 5 5 6 5 2 6 5 4 4 1 6 4 4 4 0 6 3 5 2 1 5 5 6 6 4 2 3 6 7 3 2 5 5 7 3 2 4 4 7 1 5 6 4 6 1 5 7 4 5 1 6 4 6 5 1 3 4 7 6 In the following two examples, an instance of

29、 HomogeneousTexture is embedded in the GofGopFeature datatype. In the first example, there is no specification of aggregation method. 19 20 103 87 99 130 97 73 112 109 122 132 108 102 105 113 106 141 103 111 78 76 82 117 88 70 69 61 48 68 48 53 106 84 94 130 94 75 107 104 117 128 100 99 97 107 92 13

30、2 90 106 76 64 78 110 83 65 64 52 39 72 35 47 In the second example, “Median” is used to aggregate descriptions. 19 20 103 87 99 130 97 73 112 109 122 132 108 102 105 113 106 141 103 111 78 76 82 117 88 70 69 61 48 68 48 53 106 84 94 130 94 75 107 104 117 128 100 99 97 107 92 132 90 106 76 64 78 110

31、 83 65 64 52 39 72 35 47 5.7.3 Conditions of Usage There are no specific conditions and limitations on the use of this container datatype. ISO/IEC TR 15938-8:2002/Amd.1:2004(E) ISO/IEC 2004 All rights reserved 5Add after subclause 6.8: 6.9 Color Temperature The color temperature of an image specifie

32、s the color of illumination in the scene of the image. It is expressed by Kelvin (K) temperature scale in the 1667K, 25000K range. Using this, the color temperature descriptor describes the perceptual temperature feeling of an image. It targets the perception-based image browsing that enables viewer

33、s to navigate and match images based on the temperature perception (i.e. hot, warm, moderate, and cool) of the image. This descriptor is also useful when a user would like to change the illumination of scene (i.e. still images or video) in favor of the users preference. For example, some people migh

34、t want to see warmer images (e.g. taken under incandescent lights) than original images while some people might want to see cooler images (e.g. taken under bright daylights). Those effects can be automatically achieved by adjusting the color temperature. 6.9.1 Color Temperature Browsing 6.9.1.1 Feat

35、ure Extraction The (correlated) color temperature of the scene-illumination in the image is extracted as follows. Note: In this section, several references are made to sRGB, perceived illuminant, and (correlated) color temperature and its reciprocal scale. All information on these subjects can be fo

36、und in AMD1-1AMD1-2 AMD1-3AMD1-4AMD1-5. 6.9.1.1.1 The Overall View of Color Temperature Extraction Algorithm 1) Linearizing input image: RGB null RlGlBl2) Converting RlGlBlinto XYZ 3) Removing pixels that have the pixel value smaller than the low luminance threshold(Tll) 4) Averaging XYZ value for a

37、ll remained pixels: XaYaZa5) Calculating the self-luminous threshold: sssTTTZYX , , If sssTTTZYX , , have the same values with the previous values, go to procedure 7), else remove pixels that have the pixel value bigger than the self-luminous threshold and repeat procedure 4) to 6) 6) Averaging XYZ

38、value for all pixels remained, estimating it as the illuminant tri-stimulus values, and computing the scene-illuminant chromaticity coordinates (xs, ys) in CIE 1931 diagram 7) Converting the scene-illuminant chromaticity (xs, ys) into color temperature Tc(1) Calculating the chromaticity coordinates

39、(us, vs) in CIE 1960 UCS diagram from (xs, ys) (2) Finding two adjacent isotemperature lines from (us, vs) and obtaining the distance from those lines (3) Computing the correlated color temperature using the distance ratio 6.9.1.1.2 The Detail of Extraction Algorithm 1) Linearizing input image: Obta

40、in the linearized RlGlBlfrom the inverse gamma correction of the input RGB, which is the gamma-corrected for display devices ISO/IEC TR 15938-8:2002/Amd.1:2004(E) 6 ISO/IEC 2004 All rights reservedNote, it is assumed that an input image RGB is a gamma-corrected non-linear sRGB in the range of 0255(8

41、bit) in the following equations. if () () () 0.25503928.0,jiBjiGjiR sRGBsRGBsRGB , ()()()()()()92.12255,92.12255,92.12255,=jiBjiBjiGjiGjiRjiRsRGBsRGBsRGBsRGBsRGBsRGB, else () () () 0.25503928.0,jiBjiGjiR sRGBsRGBsRGB , () ()()() ()()() ()()4.24.24.2055.1055.0255,055.1055.0255,055.1055.0255,+=+=+=jiB

42、jiBjiBjiGjiGjiGjiRjiRjiRsRGBsRGBlsRGBsRGBlsRGBsRGBl, where (i,j) is the index for pixels 2) Converting linearized RlGlBlinto CIE 1931 tristimulus XYZ with conversion matrix M ()()()()()()=jiBjiGjiRjiZjiYjiXlll, where conversion matrix =9505.01192.00193.00722.07152.02126.01805.03576.04124.0M . 3) Rem

43、oving pixels that have the pixel value smaller than the low luminance threshold(Tll) =255),( , 0),( ,),(or ),(or ),(jipotherwisejipZjiZYjiYXjiXsssTTT repeat 4) 6) where t means the iteration time for the Tsand the initial values are set to 0)(,0)0( ,0)0( = tZYXsssTTT. 7) Averaging the XYZ value for

44、all pixels remained, estimating it as an illuminant tri-stimulus value, and computing the scene-illuminant chromaticity coordinates (xs, ys) in CIE 1931 diagram. Again, row * col intuitively means the number of all pixels remained, which have p(i, j) = 255. ISO/IEC TR 15938-8:2002/Amd.1:2004(E) 8 IS

45、O/IEC 2004 All rights reserved.),()(1,),()(1,),()(1101010101010=rowicoljsrowicoljsrowicoljsjiZcolrowZjiYcolrowYjiXcolrowX.,ssssssssssZYXYyZYXXx+=+=8) Converting the scene-illuminant chromaticity (xs, ys) into color temperature Tc. (1) Calculating the chromaticity coordinates (us, vs) in CIE 1960 UCS

46、 diagram from (xs, ys). .31226,31224+=+=ssssssssyxyvyxxu(2) Finding two adjacent isotemperature lines Mori et al (1968) from (us, vs) and obtaining the distance from those lines: if (us, vs) is located between i-th and i+1-th isotemperature line then di / di+1 color temperature browsing function Fin

47、dHot() dom = ColorTemperature.XMLDocument; node = dom.getElementsByTagName(“Image”) ; resulth = “”; result.innerHTML = “”; node = SortAscendingOrder(node); for (i=0;i ”; if (resulth = “”) result.innerHTML = “ function FindWarm() dom = ColorTemperature.XMLDocument; node = dom.getElementsByTagName(“Im

48、age”) ; node=RearrangeNearToFar(node); resulth = “”; result.innerHTML = “”; for (i=0;i ”; if (resulth = “”) result.innerHTML = “ function FindModerate() dom = ColorTemperature.XMLDocument; node = dom.getElementsByTagName(“Image”) ; node = RearrangeNearToFar(node); resulth = “”; result.innerHTML = “”; for (i=0;i ”; if (resulth = “”) result.innerHTML = “ function FindCool() dom = ColorTemperature.XMLDocument; node = dom.getElementsByTagName(“Image”) ; node = SortDescendingOrder(node); resulth = “”; result.innerHTML = “”; for (i=0;i ”; if (resulth = “”) result.