Today’s Topics

• Image and video processing• Image and video applications

Image Processing: Color• Color histograms – how

much of each color is in image– Probability of a pixel in the

image being a particular color• Color correlograms – how

close colors are to each other in image– Probability of finding a pixel

of a particular color at a specific distance from a pixel of a known color

Image/Video Processing: Subdividing

• Region subdivision– Sometimes we subdivide

images into regions– Spread observed features

at edges for more continuous model

• Temporal subdivision– Video is subdivided into

segments– Spread features into

neighboring segments

4

Image Processing: Foreground Background Separation

• Background Modeling– Convert to greyscale– Dynamic model (to cope with changes in signer

body position and lighting)• BPt = .96 * BP(t-1) + .04 P

• Foreground object detection– Pixels different from background model by more

than a threshold are foreground pixels– Spatial filter removes regions of foreground pixels

smaller than a minimum threshold

• Face location to determine position of foreground relative to the face

• Videos without a single main face are not considered as potential SL videos

Image Processing: Other Features

• Edge detection– Sobel filter

• Object and Face detection– Skintone models

• Face recognition• Open Source

Computer Vision (OpenCV)

Example Applications

• MediaGlow– Clustering and selecting images from collection

• DOTS– Interpreting surveillance video

• HyperHitchcock– Authoring and viewing interactive video

MediaGLOW: The Concept

• Task and Opportunity– Many tasks involving photo sharing or publication involve grouping a

candidate photos into categories and selecting from among these groups.

– There are many different reasons to group photos: based on event, location, subject matter, visual characteristics, etc.

– There is the potential for systems to observe earlier user activity and expression to aid their later activity.

MediaGLOW: Interpreting User Action

• Evolving Notion of Similarity via User Expression– Photos presented in a graph-based

workspace with “springs” between each pair of photos.

– Lengths of springs is initially based on a default distance metric based on their time, location, tags, or visual features.

– Users can pin photos in place and create piles of photos.

– Distance metric to piles change as new members are added, resulting in the dynamic layout of unpinned photos in the workspace.

MediaGLOW: Multi-faceted Visualizationof Photo Collections

• System Expression through Neighborhoods– Piles have neighborhood for photos

that are similar to the pile based on the pile’s unique distance metric.

– Photos in a neighborhood are only connected to other photos in the neighborhood, enabling piles to be moved independent of each other.

– Lingering over a pile visualizes how similar other piles are to that pile, indicating system ambiguity in categories.

DOTS: Supporting Use of Surveillance Video

• The problem– Number and size of

surveillance systems are increasing but human attention is limiting factor

• Approach– Provide summaries

of action– Build interfaces

knowing limits of automation

– https://www.youtube.com/watch?v=9wVAVm8-bQ8

DOTS: The Main Interface

• Components– Rotating camera

bank with activity graphs

– Mixed-initiative main viewer

– Map with tracking data

– Timeline with automatic events

DOTS: Tracking Layout

• Difficulty in tracking is that camera views are often similar

• Tracking layout places cameras around the main viewer to aid tracking

• Study showed significant improvement in tracking success over traditional viewer

• In either layout, map can be used to find activity near a location and time.

HyperHitchcock: Interactive Video

• Issue– Vision: Seamlessly interact

with charactersin the show

– Reality: Difficult to author even simpleinteractive videos

• Today, video is included within pages of content but links between playing videos are not common.

Support for Hypervideo Authoring

• Links in video can lead to other video segments– Short main video with branches providing additional detail– Hyperlinks to branches just like in Web pages– Making of a scene in a movie, biography of an actor,

different camera angle• General hypervideo difficult to author

– Simple hypervideo format with only a single active link• Novel approach: use automatic video analysis, create

an easy-to-use interface, and support simple hypervideo format

Uses of Hypervideo

• Hypervideo well-suited for training video– Overview of topic with links to more detail– Viewers can choose video content based on their prior

knowledge and current task• Home video is more enjoyable if viewers can select

content– Only a small portion of the video is really “usable”– Difficult to watch long home videos – Customize viewing experience for different viewers– More detail on sports events for some family members,

more scenes with children for others

Detail-on-demand Hypervideo

• General hypervideo– Links from objects in video to other video– Requires object tracking– Requires interface for indicating and selecting from

multiple links

• Detail-on-demand video– Single link from any video segment– No anchor regions to simplify viewing and authoring– https://www.youtube.com/watch?v=LaXZuLA-68g

Hierarchical Video with Links

• Video sequences are represented as a containment hierarchy of video elements– Elements are video clips or composites grouping other video elements– Elements are played in sequence

• Each element can be link anchor or link destination• Anchor for innermost element is available while element is

playing• After link destination

video is played,play-back continuesat the link anchor

Detail-on-demand Links• Any video clip or composite can be link anchor or link destination• Optional link offsets into destination• Links have labels• Link return behaviors control the purpose of the link

– Play from where the viewer left the video– Play from the end of the source anchor sequence– Play from beginning of the

source anchor sequence– Stop playback

• Different behaviors fordestination completion oraborted playback

Hyper-Hitchcock Editor & Player Goals

• Hyper-Hitchcock editor designed to– Reduce cost of producing

interactive video– Make resulting video useful

to wider audience

• Simple video player to simulate DVD viewing experience

Hyper-Hitchcock Editor

• Hyper-Hitchcock evolved from Hitchcock video editor• Video clips grouped in piles by similarity (e.g., recording time)• Workspace to arrange clips

– Resize keyframes to trim clips– Clips ordered as horizontal

or vertical lists– Place links between clips– Group clips into composites

• Tree view to visualizecontainment hierarchy ofcomposites

Determining Suitable Video Clips• Unsuitability score

– Single score for video features such as camera motion and brightness– Estimate camera pan by shifting frames against each other– Require minimum brightness

• Determine clip boundaries– Select clips that fall in “valleys” between unsuitability peaks – Look for areas completely above unsuitability threshold

• Peak is clip boundary candidate– Enforce the minimum length requirement

• Trimming clips– Select portion of clip with minimal area under the curve– Expand the area for longer requested portions

Selected Clip Portions

Trimming Clips in the Workspace

• Best five seconds of clip selected by default• Resizing keyframe changes length of clip

– Picks the best portion around initial five-second portion– Start and end can jump to sentence boundary silence

• Clip start and/or end can be locked in timeline• Locked ends can be dragged• Audio energy

visualized in timelineto spot words andsentences

Video clips to be grouped into a composite(keyframe area proportional to clip length)

Composite visualizations

cross(area error minimized)

sliding dividers(area proportional to clip length)

Visualizing Video Composites

Attaching Links to Clips and Composites

• Link anchors and destinations can be clips, composites, or elements inside composites

• Color-coding and position indicates link attachment in workspace

Links in and out of compositeBlue: attached to compositeRed: attached to elementDashed: between composite and element

Hypervideo Player• Video player with controls for following and returning

from links• Several improvements based on user feedback

– First version indicated linksin timeline and showed thelabel for the active link

– Next version showedlabels in timeline

– Current version includeskeyframes for active linkand for link history

• User study suggestsfurther improvements

Navigation Aids in Hypervideo Player

• Keyframe list for navigation history– Shows followed links with more remote

navigation indicated by size of keyframe– Label of followed link as video caption

• Link indicator in timeline (in blue)– Link labels and keyframes in timeline– Keyframe grows, label completes, and

link recolored when active

Impressions from Users• Pilot editing study with two participants

– Subjects own video• report on a trip to Japan• family outing to mountain bike race

– Few problems but link return behaviorwas confusing for one participant

• Study of hypervideo player (6 subjects)– Plumbing training video re-authored

as hypervideo– All participants were able to find answers

quickly in the hypervideo (9 - 20 minutes in 60-minute video)– Navigation through video can be confusing. As player was altered

to better support navigation, playback becomes less like video.

Generating Hypervideo Summaries

• Locating content in video is time consuming.– Much effort into generating “good” video

summaries.– But what is good for one task is not good for

another.• Generate hypervideo summaries that allow

users to determine the level of detail viewed.

Process for Generating Summaries

• Determine number of summary levels– Based on length of source video

• Select clips to include in each summary level– Clips found by subdividing takes by camera motion– Select clips via clip distribution, take distribution, or best-

first algorithms

• Add links between summary levels– Group clips by takes– Links between clips from the same take using simple take-

to-take or take-to-take with offsets algorithms

• Selecting n clips out of m candidate clips– Evenly distribute in among candidate clips

– Selects more clips from takes with many recognized clips.– Good when take includes more than one topic/activity.– Bad when lots of clips are for a single topic/activity.

Clip Distribution Selection

Evenly distribute in time and takes Divide video duration into n time segments Select clip nearest center of segment in take not already

represented.

Bad when take includes more than one topic/activity. Good when lots of clips are for a single topic/activity.

Take Distribution for Clip Selection

Best-first Clip Selection

Assumes human or automated ordering of value of clipsSimply selects n best clips

Good in cases of edited video – not currently applicable for unedited video.Best can be introductory materialBest can be highlights of material

Links in Video Summary• All clips from a take are grouped into composite• Single clip from take or take composite is used as link

anchor and destination• Simple take-to-take algorithm

– Links take composite to take composite– Best when single activity divided into multiple clips.

• Take-to-take with offsets algorithm– Each clip from take links to take composite in next level

with offset to temporally closest clip. – Best when clips portray

multiple activities in take.• Complete takes for

entire video

Automatically Generated Summary

0:33

3:35

14:44

60:42

A four-level hypervideo summary of a one-hour source video. Lower levels provide more detail.

Time

Hypervideo in Practice

Experience with Use

• Nine hypervideos each authored by 1-2 students in a Computers and New Media class

• Recorded up to 1 hour using a DV camera then authored hypervideo in HH

• Students had about 1 week for authoring activity.

Riding Down University DriveMost directly maps geographic structure

Links are choices to stop in at sites along road.

“In Danger” BuildingsVisits to buildings identified for demolition on TAMU

campus.

Links are to seeing interior and details.

Perspectives on Bridges

Shows bridges between College Station and Austin.

Presents different perspectives (roadway, construction, wildlife) in order.

Links are to seeing different perspective.

International Dance FestivalShows bits of performances.

Brief “how-to use hypervideo player” at start.

Links are to seeing more and to next performance.

Game WalkthroughShows what happens while playing game.

Links represent choice points in game.

Music Hypervideopublic-domain video, remixed audio

Home Hypervideoidiosyncratic structure

Roles of Links

• Detail Links• Prerequisite Links• Related Information

Links• Alternate View Links• Action Choice Links

Summary

• Hyper-Hitchcock used to author documentary, how-to, music, and home hypervideos.

• Links in hypervideos used for: details, prerequisites, alternate views, action choices, and related information.

• Structures in hypervideo were impacted by the inclusion of return behaviors.

Conclusions

• Detail-on-demand video well-suited for training and home video– Simple interaction style appropriate for

DVD-player interfaces– Enables wide range of authors due to emphasis on ease of learning

and use over richness of interaction

• Hypervideo summaries – Remove need for single context-free video summary– Multiple clip selection and link generation algorithms– Act as starting point for human-authored summary

• Hyper-Hitchcock used to author documentary, how-to, music, and home hypervideos

• Links in hypervideos used for: details, prerequisites, alternate views, action choices, and related information

Today’s Topics

• Image and video processing– Color-oriented representations– Region and temporal segmentation– Foreground-background separation– Edge and face detection

• Image and video applications– MediaGlow – image selection– DOTS – surveillance– HyperHitchcock – interactive video