Object recognition using alignment
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Object Recognition Using Alignment. Brian J. Stankiewicz. Approaches to Human Object Recognition. Alignment Approach Store image(s) in memory Use image transformations to bring new view into alignment with viewed image. Approaches to Human Object Recognition. Alignment Approach.

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Object Recognition Using Alignment

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Object Recognition Using Alignment

Brian J. Stankiewicz

Approaches to Human Object Recognition

  • Alignment Approach

    • Store image(s) in memory

    • Use image transformations to bring new view into alignment with viewed image.

Approaches to Human Object Recognition

  • Alignment Approach

Template matching Failures

Approaches to Human Object Recognition

  • Alignment Approach

Many different exemplars of category of object. How does one handle this type of variability?

Approaches to Human Object Recognition

  • Structural Description

    • Pre-process image before storing in memory

    • Decompose object into simple parts

    • Describe the object’s shape in terms of their parts

      • Parts are described using specific non-accidental properties

Structural Descriptions

  • Objects are decomposed into “parts”.

  • Objects are described by specifying configuration of parts and their relations.

Structural Descriptions

  • Each part is describe by specifying the values of particular shape parameters.

  • Varying parameter varies the shape.

Structural Descriptions

  • Challenge.

    • How do you decompose image into objects and objects into parts?

    • How do you determine the shape parameters of a part given an image.

      • This topic will be covered next week in Biederman and Biederman & Cooper papers.


  • Begin by investigating the effect of viewpoint on object recognition.

    • Look for evidence of alignment approach

    • Shepard & Metzler

      • Mental rotation of 3d shapes

      • Picture Plane and Depth rotations

    • Tarr & Pinker

      • Mental rotation of 2d shapes

      • Picture plane rotation only

      • Multiple-Views Hypothesis

Shepard & Metzler

  • Wanted to understand how humans recognize different views of the same object.

    • Different images of same 3D shape can be produced by manipulating viewpoint

  • Investigated the effect of depth and picture-plane rotations.

Same/Different Paraidgm

Shepard & Metzler: Stimuli

  • “Novel” stimuli: Not a lot of previous experience

  • Fairly difficult task

    • Cannot simply use simple features

  • Able to carefully control view information.

Shepard & Metzler: Procedure

  • Two images presented simultaneously

    • Images of identical or “mirror reflected” objects

  • Subjects indicated whether two images depicted same object

    • Responded by pulling a “lever”

  • Record response times

Shepard & Metzler: Results

  • Response times increased linearly with orientation

  • Suggests that subjects are “mentally rotating” images to determine match.

RT To “Same” Responses

Angle of Rotation

Shepard & Metzler: Results

  • Reaction times increased linearly with depth orientation

  • Suggests a similar mechanism

Shepard & Metzler: Results

  • Not only are both depth and picture-plane rotations linearly increasing, but they have very similar slopes.

  • Suggestive of a single “mental rotation” mechanism.

Object recognition

  • Two fundamental approaches to human object recognition

    • Alignment approaches

      • Object recognition through alignment process

    • Structural description approach

      • Decomposition of features included in an object

      • Describe the objects’ shape in terms of their parts and relation among the parts.

What is alignment

  • Definition

    • A process that transform stored images to bring new view into alignment with viewed image.

  • Why we need alignment?

    • We cannot recognize object exactly only by template matching

    • Need for some process which transform input images or data  alignment

2 studies in alignment approaches

  • Shepard & Metzler

    • Mental rotation of 3D objects shapes

    • A single mental rotation mechanism

    • Evidence*: same results from rotated depth and picture-plane pairs.

  • Tarr & Pinker

    • Multiple view hypothesis (?)

Tarr & Pinker

  • Wanted to investigate “mental rotation” in more detail

    • Two hypotheses

      • Single canonical image stored in memory and all new images are aligned to that single representation

      • Multiple-Views stored in memory.

        • Align new view to closest stored view

Tarr & Pinker: Method

  • Train subjects to recognize small set of novel, letter-like objects.

    • Did a “handedness” task

    • Is the image the trained image (standard)or its mirror reversal?

Tarr & Pinker: Stimuli

  • Novel, letter-like images.

  • Subjects trained on 3 of the images

    • Reduce stimuli specific effects

Tarr & Pinker: Procedure

  • Trained subjects on 4 different orientations

    • (0°,45°,-90°,135°)

  • Tested on trained and “surprise orientations”

  • Measured response times

Initial reaction times similar to S&M

Performance improves after 13 blocks

Surprise orientations slower than trained

Tarr & Pinker: Exp. 1 Results

Block 1~12: practice

Block 13: practice + surprise

Tarr & Pinker: Exp. 1 Results

Compute best fittingline to compute slope

Surprise orientations’ required degree to be rotated 90 : 45 - 135: 45 - 45 : 45 but 180: 90

“4 different orientation- images stored in memory?”

Tarr & Pinker: Exp. 1 Results

High slope = much rotation = single canonical image

Tarr & Pinker: Exp. 1 Summary

  • Stimuli showed a similar result to previous findings

    • Increased RT with disparate orientations from training

    • Subjects showed improvement following training

    • Even after training, subjects were slower on non-trained (intermediate) orientations

Tarr & Pinker: Exp. 2 Motivation

  • Demonstrated an improvement in recognition times with training.

    • Not a demonstration of canonical or multiple views.

    • Experiment 2, train on a few orientations and test on multiple orientations.

    • See if there is evidence for rotating to the “nearest” trained orientation.

Tarr & Pinker: Methods

  • Similar to Experiment 1

    • However, classification task rather than “handedness” task.

      • Three objects: “Kip”, “Kef”, “Kor”, and distractors

    • Record response times

Tarr & Pinker: Exp. 2 Procedure

  • Train on 3 orientations

  • Test on multiple intervening orientations

  • Look for rotation functions to nearest trained orientation

Tarr & Pinker: Exp. 2 Results

Tarr & Pinker: Exp. 2 Summary

  • Investigated whether subjects show a linearly increasing RT to canonical view or closest trained view.

    • Showed mixed evidence.

    • For 0° and 210° it appears that there is a dip in the surrounding RTs

      • Suggests rotation to nearest orientation

    • For 105° no evidence of alignment.

Mental Rotation in Block 1

By block 13 trained orns are fast

Mental rotation rate for untrained orns slower.

Tarr & Pinker: Exp. 2 Results

Tarr & Pinker: Study 3

  • Wanted to see if “handedness” played a role in recognition times.

    • Experiment 1 showed effect for handedness judgment.

    • Subjects might engage in handedness judgment unnecessarily.

    • Trained on both “standard” and “reversed” images

    • Tested on both set of images

      • No handedness judgment required

Tarr & Pinker: Exp. 3 Results

90 

-135 


- 45

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