ICCV 2005 Beijing, Short Course, Oct 15

ICCV 2005 Beijing, Short Course, Oct 15

Agenda Introduction Bag-of-words models Visual words with spatial location Part-based models Discriminative methods Segmentation and recognition Recognition-based image retrieval Datasets & Conclusions Databases Caltech 101 Caltech 256 Pascal Visual Object Classes (VOC) LabelMe Slides from Andrew Zisserman Caltech 101 Pictures of objects belonging to 101 categories. About 40 to 800 images per category. Most categories have about 50 images.

The size of each image is roughly 300 x 200 pixels. Collected in September 2003 by Fei-Fei Li, Marco Andreetto, and Marc 'Aurelio Ranzato. Train on 5, 10, 15, 20 or 30 images Test on rest report results per class Caltech 101 images Caltech-101: Drawbacks Smallest category size is 31 images: Too easy? left-right aligned Rotation artifacts Soon will saturate performance N train 30

Caltech-256 Smallest category size now 80 images About 30K images Harder Not left-right aligned No artifacts Performance is halved More categories New and larger clutter category traffic light kayac basketball-hoop dog baseball-bat Caltech 256 images The PASCAL Visual Object Classes

(VOC) Dataset and Challenge Mark Everingham Luc Van Gool Chris Williams John Winn Andrew Zisserman The PASCAL VOC Challenge Challenge in visual object recognition funded by PASCAL network of excellence Publicly available dataset of annotated images. Development kit available. Main competitions in classification (is there an X in this image) and detection (where are the Xs) Taster competitions in segmentation and 2-D human pose estimation (2007-present) Dataset Content 20 classes: aeroplane, bicycle, boat, bottle, bus, car, cat, chair,

cow, dining table, dog, horse, motorbike, person, potted plant, sheep, train, TV Real images downloaded from flickr, not filtered for quality Complex scenes, scale, pose, lighting, occlusion, ... Annotation Complete annotation of all objects Annotated in one session with written guidelines Occluded Object is significantly occluded within BB Truncated Object extends beyond BB Difficult

Not scored in evaluation Pose Facing left Examples Aeroplane Bicycle Bus Car Bird Cat Boat

Chair Bottle Cow History Images Objects Classes Entries 2005 2,232 2,871

4 12 Collection of existing and some new data. 2006 5,304 9,507 10 25 Completely new dataset from flickr (+MSRC)

2007 9,963 24,640 20 28 Increased classes to 20. Introduced tasters. 2008 8,776 20,739 20 Added occlusion flag. Reuse of taster data. Release detailed results to support meta-analysis

New dataset annotated annually Annotation of test set is withheld until after challenge Main Challenge Tasks Classification Is there a dog in this image? Evaluation by precision/recall Detection Localize all the people (if any) in this image Evaluation by precision/recall based on bounding box overlap Example Precision/Recall: 2007 Person detection 1 IRISA (0.221) UoCTTI (0.213)

INRIA_Normal (0.121) MPI_ESSOL (0.117) INRIA_PlusClass (0.092) MPI_Center (0.091) TKK (0.061) 0.9 0.8 0.7 precision 0.6 0.5 0.4 0.3 0.2 0.1 0 0

0.1 0.2 0.3 0.4 0.5 recall 0.6 0.7 0.8 0.9 1

LabelMe Russell, Torralba, Freman, 2005 Links to datasets The next tables summarize some of the available datasets for training and testing object detection and recognition algorithms. These lists are far from exhaustive. Databases for object localization CMU/MIT frontal faces vasc.ri.cmu.edu/idb/html/face/frontal_images cbcl.mit.edu/software-datasets/FaceData2.html Patches Frontal faces Graz-02 Database www.emt.tugraz.at/~pinz/data/GRAZ_02/

Segmentation masks Bikes, cars, people UIUC Image Database l2r.cs.uiuc.edu/~cogcomp/Data/Car/ Bounding boxes Cars TU Darmstadt Database www.vision.ethz.ch/leibe/data/ Segmentation masks Motorbikes, cars, cows

LabelMe dataset people.csail.mit.edu/brussell/research/LabelMe/intro.html Polygonal boundary >500 Categories Databases for object recognition Caltech 101 www.vision.caltech.edu/Image_Datasets/Caltech101/Caltech101.html Segmentation masks 101 categories Caltech 256 http://www.vision.caltech.edu/Image_Datasets/Caltech256/

Bounding Box 256 Categories COIL-100 www1.cs.columbia.edu/CAVE/research/softlib/coil-100.html Patches 100 instances NORB www.cs.nyu.edu/~ylclab/data/norb-v1.0/ Bounding box 50 toys On-line annotation tools

ESP game www.espgame.org Global image descriptions Web images LabelMe people.csail.mit.edu/brussell/research/LabelMe/intro.html Polygonal boundary High resolution images http://www.pascal-network.org/challenges/VOC/ Segmentation, boxes various

Collections PASCAL Topics not covered Context Scene Inter-object relations Video Tracking & detection Multiple viewpoints Summary Methods reviewed here

Bag of words Bag of words with location Parts and structure Discriminative methods Combined Segmentation and recognition Recognition for retrieval Resources online: http://cs.nyu.edu/~fergus/icml_tutorial Slides Code Links to datasets

Recently Viewed Presentations

  • STRUCTURAL STABILITY - Purdue Engineering

    STRUCTURAL STABILITY - Purdue Engineering

    The structure stiffness decreases to zero and becomes negative. The load capacity is reached when the stiffness becomes zero. Neutral equilibrium when stiffness becomes zero and unstable equilibrium when stiffness is negative. Structural stability failure - when stiffness becomes negative.
  • "Fall" into Deductions - IN.gov

    "Fall" into Deductions - IN.gov

    a homestead deduction in the person's name as an individual or a spouse; or. a deduction under the law of another state equivalent to the homestead deduction in Indiana; the person must file a certified statement with the auditor of...
  • Glass-Steagall Act vs. Gramm Leach Bliley Act

    Glass-Steagall Act vs. Gramm Leach Bliley Act

    Today's Implications. 4/12/2011. BA 543 - Lauren Jespersen. Senator Phil Gramm defends his bill by saying "...if GLB was the problem, the crisis would have been expected to have originated in Europe where they never had Glass-Steagall requirements to begin...
  • Chapter 14 Leadership - TTU :: RCOBA :: Jerry Stevens

    Chapter 14 Leadership - TTU :: RCOBA :: Jerry Stevens

    For example, according to trait theory, leaders were commonly thought to be taller, more confident, and have greater physical stamina (i.e., higher energy levels). Trait theory is also known as the "great person" theory, because early versions of trait theory...
  • Solar Cell Testing

    Solar Cell Testing

    Arial Calibri Georgia Symbol Office Theme PowerPoint Presentation BASIC SOLAR CELL TESTING Basic Structure of a Solar Cell Basic Photovoltaic Cell Model Key Parameters A Solar cell is a diode Standard Test Conditions Sunlight Simulator in Clean Room Procedure for...
  • Client/Server Computing - Rivier University

    Client/Server Computing - Rivier University

    Access authentication (for example, logging into a server) Session Management Verification that adequate disk space is available for a request Notifying a user that a printer is offline Examples: Various Remote Procedure Calls (RPCs) used by network operating systems.
  • Castell ENW Daniel Roberts CYFEIRIAD 7 Heol y

    Castell ENW Daniel Roberts CYFEIRIAD 7 Heol y

    ENW Daniel Roberts CYFEIRIAD 7 Heol y Castle, Amroth RHIF FFÔN saeth tri dim dim un dai OED Un deg pimp oed PENBLWYDD Ionwr 24 ENW'R YSGOL Ysgol Greenhill School PYNCIAU YSGOL Hannes, celf, cymreag PROFIAD O WEITHIO Es i...
  • Topic 5 - Boggs Biology

    Topic 5 - Boggs Biology

    Annelida - segmented worms. Mollusca - snails, clams, octopuses. Arthropoda - insects, spiders and crustaceans. ... A diagram showing cladistics, sort of like a family tree. The point of branching, where the common ancestor is located is called a node.