ENEE408G Capstone -- Multimedia Signal Processing (F'05) Video Analysis, Processing & Communications Fall’05 Instructor: Carol Espy-Wilson Electrical &

ENEE408G Capstone -- Multimedia Signal Processing (F'05)

Video Analysis, Processing & CommunicationsVideo Analysis, Processing & Communications

Fall’05 Instructor: Carol Espy-Wilson

Electrical & Computer Engineering

University of Maryland, College Park

http://www.ece.umd.edu/class/enee408g/

[email protected]

ENEE408G Fall 2005ENEE408G Fall 2005Lecture-9Lecture-9

ENEE408G Capstone -- Multimedia Signal Processing (F'05)Lec9 – Video Proc/Analysis/Comm.

4/7/04 [2]

Last LectureLast Lecture

Motion estimation and compensation

Hybrid video coding/compression– MPEG-1 video coding

Today:– Video content analysis

– Different coding approaches and representations of video

– Overview: video capturing and display

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Video Content AnalysisVideo Content Analysis


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Introduction to Video Content AnalysisIntroduction to Video Content Analysis

Teach computer to “understand” video content– Define features that computer can learn to measure and compare

color (RGB values or other color coordinates) motion (magnitude and directions) shape (contours) texture and patterns

– Give example correspondences so that computer can learn build connections between feature & higher-level

semantics/concepts statistical classification and recognition techniques

Video understanding– Break a video sequence into chunks, each with consistent content ~ “shot”

– Group similar shots into scenes that represent certain events

– Describe connections among scenes via story boards or scene graphs

– Associate shot/scene with representative feature/semantics for future query

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Video Understanding (step-1)Video Understanding (step-1)

– Break a video sequence into chunks, each with consistent content ~ “shot”

From Yeung-Yeo-Liu: STG (Princeton)


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– Group similar shot into scenes



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– Describe connections among scenes via story boards or scene graphs



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Video Temporal SegmentationVideo Temporal Segmentation

A first step toward video content understanding

Two types of transitions

– “Cut” ~ abrupt transition

– Gradual transition Fade out and Fade in; Dissolve; Wipe

– Demo

Detecting transitions

– Detecting cut is relatively easier ~ check frame-wise difference

– Detecting dissolve and fade by checking linearity f0 (1 – t/T) + f1 * t/T

– Detecting wipe ~ more difficult via projection, edge pattern, or linearity of color

histogram

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4/7/04 [9]

Types of TransitionsTypes of Transitions

– [above] Transition types offered by Adobe Premiere

– See also transition demos provided by PowerPoint

From talks by Joyce-Liu (Princeton)

Video transition collection (Rob Joyce) www.ee.princeton.edu/~robjoyce/research/transitions/


4/7/04 [11]

Compressed-Domain ProcessingCompressed-Domain Processing

Use I & P frames only to reduce computation and to enhance robustness in scene change detection– … I b b P b b P b b P b b I b b P …

Working in compressed domain– Process video by only doing partial decoding (inverse VLC,

etc.) without a full decoding (IDCT) to save computation

Low resolution version already provide enough information for transition detection– DC-image (spatially-reduced versions of the original image)

(i,j) pixcel in the dc image is the average value of the (i.j) block in the original image

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DC ImageDC Image– Put DC of each block together

– Already contains most information of the video

DC Frame

Example From Joyce-Liu (Princeton)


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Fast Extraction of DC Image From MPEG-1Fast Extraction of DC Image From MPEG-1

I frame– Take DC coeff. from each block and put together

P/B frame– Fast approximation of reference block’s DC

– Adding DC of the motion compensation residue recall DCT is a linear transform

[ ( )] [ ( )] [ ( )]DCT P DCT P DCT Pcur ref diff00 00 00

[ ( )] [ ( )]DCT Ph w

DCT Prefi i

ii

00 001

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Compressed-Domain Scene Change DetectionCompressed-Domain Scene Change Detection

Compare nearby frames– Take pixel-wise difference of nearby DC-frames

– Or take pixel-wise difference of every N frames to accumulate more changes => useful for detecting gradual transitions

Observe the pixel-wise difference for different frame pairs– Peaks @ cuts, and plateaus @ gradual transitions Figure from Yeo-Liu

CSVT’95 paper

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4/7/04 [15]

Scene Change Detection (cont’d)Scene Change Detection (cont’d)

Figure from Yeo-Liu CSVT’95 paper

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4/7/04 [18]

Wipe Detection (cont’d)Wipe Detection (cont’d) More diverse and fancy wipes

Linear change in color histogram

wipe

G k

H k

m

n

Bin 1

Bin 2

Bin 3

From talks by Joyce-Liu (Princeton)


4/7/04 [19]

Color HistogramColor Histogram

What is color histogram?– Count the # of pixels with the same color

– Plot color-value vs. corresponding pixel#

Similarly for luminance histogram

Give idea of the dominate color and color distribution– Ignore the exact spatial location of each color value

– Useful in image and video analysis

Color histogram can be used to:– Detect gradual shot transition esp. for fancy wipes

– Measure content similarity between images / video shots

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Overview of Video Capturing & Display Overview of Video Capturing & Display


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Video CameraVideo Camera

Frame-by-frame capturing

CCD sensors (Charge-Coupled Devices)– 2-D array of solid-state sensors

– Each sensor corresponding to a pixel

– Store in a buffer and sequentially read out

– Widely used small and light

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Video DisplayVideo Display

CRT (Cathode Ray Tube)– Large dynamic range

– Bulky for large display CRT physical depth has to be similar to screen width

LCD Flat-panel display– Use electrical field to change the optical properties hence the

brightness/color of liquid crystal

– Generating the electrical field by an array of transistors: active-matrix thin-film transistors by plasma

“Active-matrix display” (also known as TFT) has a transistor located at each pixel, allowing display be switched more frequently and less current to control pixel luminance. Passive matrix LCD has a grid of conductors with pixels located at the grid intersections

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4/7/04 [23]

Composite vs. Component VideoComposite vs. Component Video

Component video– Three separate signals for tristimulus color representation or luminance-

chrominance representation

– Pro: higher quality

– Con: need high bandwidth and synchronization

Composite video– Multiplex into a signal signal

– Historical reason for transmitting color TV through monochrome channel

– Pro: save bandwidth

– Con: cross talk

S-video: luminance sig. + single multiplexed chrominance sig.

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Analog Video RasterAnalog Video Raster

Line-by-line “Raster Scan”– Represent line-by-line image frame with 1-D analog

waveform

– Synchronization signal for horizontal and vertical retrace

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Forming Picture on TV Tube (Monochrome)Forming Picture on TV Tube (Monochrome)

How many lines?

From B.Liu EE330S’01 Princeton


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How Many TV Lines?How Many TV Lines?

Determined by spatial freq. response of HVS(Recall Lecture-2)

dot

dot

Cannot resolve if

distance > 2000 x separation

(~ 0.03 degree viewing angle)

From B.Liu EE330S’01 Princeton

N = 500 for D=4H


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Progressive vs. Interlaced scanProgressive vs. Interlaced scanFrom B.Liu EE330S’01 Princeton


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Analog Color TV SystemsAnalog Color TV Systems

Historical notes – Color TV system had to be compatible with earlier monochrome TV system

3 formats– NTSC ~ North American + Japan/Taiwan

– PAL ~ Western Europe + Asia(China) + Middle East

– SECAM ~ Eastern Europe + France

– What format in your home country?

From Wang’s Preprint Fig.1.5

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4/7/04 [29]

Comparison of Three Analog TV SystemsComparison of Three Analog TV Systems

– Spatial and temporal resolution

– Color coordinate

– Signal bandwidth

– Multiplexing of luminance, chrominance, and audio

(From Wang’s Book Preprint)

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NTSCNTSC

4:3 aspect ratio (width:height)

525 lines/frame, 2:1 interlace at field rate 59.94Hz– 483 active lines per frame; vertical retrace takes time of 9 lines

– rest for broadcaster’s info. like closed caption

YIQ color coordinate for transmission– RGB primary slightly different from PAL

– Orthogonal chrominance I ~ orange-to-cyan; Q ~ green-to-purple (need less

bandwidth)

Multiplexing over 6M Hz total bandwidth– Artifacts due to cross talk between luminance and chrominance

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NTSC 6MHz Bandwidth NTSC 6MHz Bandwidth From Wang’s BookPreprint Fig.1.6(b)


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Analog Video RecordingAnalog Video Recording

Comparison of common formats

From Wang’s BookPreprint Table 1.2


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Digital Video FormatsDigital Video Formats

ITU-R BT.601 recommendation Downsampled chrominance

– Y Cb Cr coordinate and four subsampling formats

Inter. Telecomm. Union – Radio sector

Wang’sBookPreprint Fig.1.8

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Summary: Source FormatsSummary: Source Formats

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Other Digital Video Coding StandardsOther Digital Video Coding Standards


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H.26x for Video TelephonyH.26x for Video Telephony Remote face-to-face communication: A dream for years

H.26x – Video coding targeted low bit rate– Through ISDN or regular analog telephone line ~ on the order of 64kbps

– Need roughly symmetric complexity on encoder and decoder

H.261 (early 1990s)– Similar to simplified MPEG-1 ~ block-based DCT/MC hybrid coder

– Integer-pel motion compensation with I/P frame only ~ no B frames

– Restricted picture size/fps format and M.V. range

H.263 (mid 1990s) and H.263+/H.263++ (late 1990s)– Support half-pel motion compensation & many options for improvement

H.264 (latest 2001-): also known as H.26L / JVT / MPEG4 part10

– Hybrid coding framework with many advanced techniques

– Focusing on greatly improving compression ratio at a cost of complexity

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MPEG-2MPEG-2

Extend from MPEG-1

Target at high-resolution high-bit-rate applications– Digital video broadcasting, HDTV, …

– Also used for DVD

Support scalability

Support interlaced video – Frame pictures vs. Field pictures

– New prediction modes for motion compensation related to interlaced video Use previously encoded fields to do M.E.-M.C.

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Scalability in Video CodecsScalability in Video Codecs

Scalability: provide different quality in a single stream– Stack up more bits on base layer to provide improved quality

Possible ways for achieving scalabilities– SNR Scalability ~ Multiple–quality video services

Basic vs. premium quality

– Spatial Scalability ~ Multiple-dimension displays Display on PDA vs. PC vs. Super-resolution display

– Temporal Scalability ~ Multiple frame rates

– Frequency Scalability ~ Blurred version to sharp, detailed version

Layered coding concept facilitates:– Unequal error protection – Efficient use of resources

– Different needs from customers – Multiple services

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SNR ScalabilitySNR Scalability

Two layers with same spatio-temporal resolution but different qualities

base-layerencoder

base-layerdecoder

enhancement-layerencoder

mul

tipl

exer+ -

Video inBase-layerbitsteam

Enhancement-layerbitsteam

Outputbitsteam

From R.Liu Seminar Course @ UMCP


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MPEG-4MPEG-4

Many functionalities targeting a variety of applications

Introduced object-based coding strategy– For better support of interactive applications & graphics/animation video

– Require encoder to perform object segmentation difficult for general applications

Introduced error resilient coding techniques– “Streaming video profile” for wireless multimedia applications

Part-10 is converged into H.264– Focused on improving compression ratio and error resilience

– Stick with Hybrid coding framework

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Object-based Coding in MPEG-4Object-based Coding in MPEG-4

Interactive functionalities

Higher compression efficiency by separately handling – Moving objects

– Unchanged background

– New regions

– M.C.-failure regions

=> “Sprite” encoding

Object segmentationneeded (not easy )– Based on color, motion,

edge, texture, etc.

Revised from R.Liu Seminar Course @ UMCPU

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Object-based Coding in MPEG-4 (cont’d)Object-based Coding in MPEG-4 (cont’d)

From Wang’s book preprint Fig. 13.30

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MPEG-7MPEG-7

“Multimedia Content Description Interface”

– Not a video coding/compression standard like previous MPEG

– Emphasize on how to describe the video content for efficient indexing, search, and retrieval

Standardize the description mechanism of content– Descriptor, Description Scheme, and Description Definition Languages

– See the Bonus Part in Design Project 2 for demos of MPEG-7 visual descriptor: Color, Texture, Shape, ……

Figure from MPEG-7 Document N4031 (March 2001)

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SummarySummary

Video content analysis

Video capturing and display

Different video coding standards

This week’s Lab session: video processing

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Reading AssignmentReading Assignment

Chapter 7 “Data Compression” (handout)– Sec. 7.6 => H.261 & H.263

– Sec. 7.7.5 & 7.7.6 => MPEG-4 & MPEG-7

Tutorial on MPEG Video Coding (handout)– IEEE Signal Processing Magazine, Sept. 1997

Yeo-Liu paper on DC-image and scene change detection– Electronic version @ course web page

Chapter 9 “Content Analysis” (by Steinmetz et al.)– Hard-copy handout; Sec. 9.1, 9.2, 9.3.2-9.3.3

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Documents

ENEE408G Capstone -- Multimedia Signal Processing (F'05) Video Analysis, Processing & Communications Fall’05 Instructor: Carol Espy-Wilson Electrical &