1ª aula

Apresentação: Organization, Program, Introduction, Querying Multimedia Databases, Application Examples

1ª aula

Apresentação: Organization, Program, Introduction, Querying Multimedia Databases, Application Examples

2ª aula

Multimedia Data: Text, Vector Graphics, 3-D Vector Graphics, Raster Graphics, Digital Image, Voxel, Audio, Digital Video

3ª aula

Fourier and Wavelets:Why do we need a Transform?, Fourier Transform and the short term Fourier (STFT), Heisenberg Uncertainty Principle, The continues Wavelet Transform, Discrete Wavelet Transform, Wavelets Transforms in Two dimensions

4ª aula

Compression principles Text and Image: Compression principles Text and Image, Lossless and lossy compression, Entropy encoding, Source encoding, Differential encoding, Text compression, Static Huffman coding, Arithmetic coding, Lempel-Ziv coding, Image compression, GIF,TIFF,JPEG

5ª aula

Audio and Video Compression: Reduction of information in the audio signal, Differential pulse code modulation (DPCM), Adaptive differential, Adaptive predictive coding (APC), Linear predictive coding (LPC), Perceptual features, Human ear, MPEG audio coders, Video, I-frame and P-frame, Motion estimation, MPEG

6ª aula

Introduction to DB, Multimedia and SQL: Why do we use Databases, Entities and Relationships, BLOB, CLOB, New Types, DataLInk, Relational DB and Multimedia, Multimedia Extender, Oracle interMedia, Contend Based Image Retrieval, Indexing

7ª aula

Human Visual System: Visible Spectrum, Human Eye, Retina, Color Sensitivity, Visual Cortex, Receptive Cells, Computational Model of Object Recognition, Hierarchical Template Matching, Dorsal (“Where”) and Ventral (“What”) Visual Streams in Human Brain, Object Recognition, Four stages of representation (Marr, 1982), Recognition by components (Geons), Saccadic Eye Movements, Attneaves Cat, The World as an Outside Memory, Memory for Menal Imagery

8ª aula

Human Acoustic Processing: Sound and Light, The Ear, Cochlea, Auditory Pathway, Speech Spectrogram, Vocal Cords, Formant Frequencies, Time Warping, Hidden Markov Models;Signal, Time and Brain; Process of temporal integration, perceptual identity (Pöppel)

9ª aula

Contend Based Multimedia Retrieval:CBIR, Query Types, Semantic Gap, Features, Segmentation, High dimension, IBMs QBIC; GIFT, MRML, Blobworld, CLUE, SIMPLIcity, CBMR, Multimedia, Automatic Video Analysis

10ª aula

Using Multimedia Metadata: Semantic Gap, Manual textual annotation, Subjective process, Meta data generation, MP3 and ID3, EXIF, Dublin Core, MPEG-7, Mpeg-7 and the semantic gap, MPEG-7 Annotation , Mpeg future, MPEG-21, Mpeg-7 and indexing

11ª aula

Feature extraction: Bi-Histogram, Binarization, Entropy, What is texture, Texture primitives, Filter banks, 2D Fourier Transform, Wavelet maxima points, Edge detection, Image gradient, Mask operators, Feature space

12ª aula

Clustering and the Curse of dimensionality: Cluster-based Image Retrieval Scheme, What is Cluster Analysis, k-Means, Adaptive Initialization, Clustering and Queering, Some confusion..., Curse of dimensionality, Principal component analysis, Dimension Reduction

13ª aula

Metric Indexes: Feature Based Similarity, B-tree, kd-trees, Minimum Bounding Rectangles - MBRs, R-trees, R-trees Search, R-trees Insertion, R-trees Split, R*-trees, SS-trees, Curse of Dimensionality, Problems of High-Dim. IndexStructures

14ª aula

Z-ordering: Reduce n-dim to 1-dim points, snake-curve, z-ordering, bit-shuffling, Linear quad trees, queries, Hilbert curve, Space filling curve, L-Systems, Fractals, Hausdorff dimension

15ª aula

GEMINI: GEneric Multimedia INdexIng, distance measure, Sub-pattern Match, ‘quick and dirty’ test , Lower bounding lemma, 1-D Time Sequences, Color histograms, Color auto-correlogram

16ª aula

Hierarchical GEMINI: GEneric Multimedia INdexIng , DB in feature space, Range Query, Linear subspace sequence method, DB in subspace, Generic constraints, Computing Cost, Orthogonal projection, Lower resolution images, Image Pyramid, Hierarchy of subspaces

17ª aula

Dealing with Text Databases: Unstructured data, Boolean queries, Sparse matrix representation, Inverted index, Counts vs. frequencies, Term frequency , tf x idf term weights, Documents as vectors, Cosine similarity, Dimensionality reduction, GEMINI , Vectors and Boolean queries

18ª aula

Probabilistic Model: Axioms of Probability, Bayes Theorem, Conditional Independence, Probability Ranking Principle, Probabilistic Retrieval Strategy, Binary Independence Model, Iteratively estimating p, Maximum likelihood Hypothesis, Naive Bayes, Stochastic Language Models, Vectors & Probability, Image query terms, When does Naive Bayes work

19ª aula

Multimodal Fusionand Evaluation: Multimodal Search, Constrained hierarchies, Early fusion, Feature vector formed by concatenation, Late fusion Weighted-sum rule, multiplication of the probabilities of the modalities, Learning of the, Importance, Measures for a search engine, User Happines, Precision/Recal

20ª aula

Associative Memory: Content-Addressable Memory; Associative Memory; Lernmatrix; Association; Heteroassociation; Learning; Retrieval; Reliability of the answer; Storage Analysis; Sparse Coding; Implementation on a Computer; Applications; Hardware

21ª aula

Semantic Representation: Semantic data models, Frames, Semantic Nets, Example of a Taxonomy, Object-relational model, Rules, Expert Systems, Example

22ª aula

Multimedia Database Architecture: Multimedia Architecture Requirements, ACID test, Multimedia Server Requirements, Distributed Multimedia System, Super server concept, Client-Server Systems, P2P, Media Streams

23ª aula

WebObjects: Static Webpage, Dynamic Website, Web Applications, Desktop Applications, Database Access, Separation of Presentation Logic, Business Logic, and Data, Scalability and Performance, Enterprise Objects, Object Instances, Java 2 Platform, Enterprise Edition, ASP.NET, Example iTunes

24ª aula

Intelligent Multimedia Databases for Medicine: HIS, CIS, HL7 (Health Level 7), DICOM (Digital Imaging and Communications in Medicine ), PACS (Picture archiving and communication systems), Electronic health record (EHR) / Electronic mediacal record (EMR), What are intelligent multimedia-databases in medicine

25ª aula

Overview: 1) Multimedia Data, 2) Fourier / Wavelet Transform, 3) Compression, 4) Relational Databases, 5) Features, 6) Indexing Methods for Feature Based Similarity, 7) AI -Techniques, 6) Architecture and Applications,