Identification of MPEG-4 FDP Patterns in Human Faces using Data-Mining Techniques

1. Perales López, F. paco.perales@uib.es Abásolo, M.J. mjabasolo@uib.es Britos, P. pbritos@itba.edu.ar García Martínez, R. rgm@itba.edu.ar MPEG-4 is an ISO/IEC standard which defines 84 feature points called Face Definition Parameters (FDPs) to parameterise a face. FDPs are used to personalize a generic face model to a particular face. MPEG-4 FDPs DATABASE OF FACES In our work a face is described by distances between different MPEG-4 FDPs. (i.e. mouth width, eyebrown width, etc.). We have a database of 600 faces of different sex, race, etc. 3.2 3.8 3.11 3.6 FW: 10.10 to 10.9 3.4 RE: 4.2 to 4.6 REH: 3.14 to 3.10 REW: 3.12 to 3.8 NH: 9.6 to 9.2 FH: 11.1 to 2.1 NT: 9.3 to 9.15 MW: 8.4 to 8.3 MH: 8.1 to 8.2 DATA MINING TECHNIQUES Data mining is all about extracting patterns from a warehoused data. Discretization of the continuous fields allows using it as an objective of the rules. C4.5 is an automatic learning algorithm for classifying examples. It obtains decision trees or sets of if-then rules forms. C5.0 is an improvement of C4.5. C5.0 C4.5 FIELD DISCRETIZATION SOM are used to classify high- dimensional data. In this work we use SOM for clustering the records. • Example: objective field “sex” • Rules obtained with C4.5 • IF weight < 63 kg. THEN sex = female • IF NA >= 81,57º THEN sex = female • IF weight >= 72 kg. THEN sex = male • IF weight < 72 kg. THEN sex = female • IF RID >= 23 mm THEN sex = male • Rules obtained with C5.0 • IF weight < 70 kg. AND LE <=79mm THEN sex = female • IF weight <= 62 kg. THEN sex = female • IF weight >= 62 kg. AND LE >79mm THEN sex = male • IF weight > 70 kg. THEN sex = male • Example: objective field discretized“FH” • Rules obtained with C4.5 • IF FW >=5 THEN FH range = 5 • IF LE >= 84mm THEN FH range = 4 • IF LEH < 40mm THEN FH range = 2 • IF NH >= 54.6mm THEN FH range = 1 • IF weight < 50 kg. THEN range = 1 • IF LID >= 25mm THEN FH range = 4 • Rules obtained with C5.0 • IF NH <= 53.9mm THEN FH range = 1 • IF LEH <= 55mm AND LE > 71mm AND MH <=21mm THEN FH range = 2 • IF LEH <= 55mm AND LE <= 71mm AND NH > 23.9mm THEN FH range = 2 • IF LEH > 55mm AND LE <= 88mm AND LID < 24mm THEN FH range = 3 • IF LEH <= 55mm AND LE > 71mm AND MH >21mm THEN FH range = 3 • IF LEH > 55mm THEN FH range = 4 SELF ORGANIZING MAPS Identification of MPEG-4 FDP Patterns in Human Faces using Data-Mining Techniques The main purpose of this work is to induce rules that describe patterns in human faces, that means relations between different dimensions of a face. • RULES FOR WHAT? • To personalize a generic face model with standard measures according some conditions like sex, race, etc. • To discover relations between different parts of a face • To discover relations between the parts of a face and other characteristics like sex, race, height, etc. • To classify an unknown face example (sex, race, etc.) Cluster vs. entire database More precise rules by analysing the main cluster instead of the whole database. C5.0 vs. C4.5 More precise rules with C5.0 than with C4.5. More complex rules with C5.0 (left part of the rule has a conjunction) than with C4.5. Work subsidized by projects: HUMODAN IST-2001-32202 • CICYT TIC2001-0931 • TIC2002-10743-E