grouping in object recognition

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Grouping in object recognition: The role of a Gestalt law in letter identification nis G., Majaj, Najib J., Raizman, Noah, Christian, Christopher J., Kim, Edward & Palomares, Melanie C Psychology and Neural Science, New York University, New York, NY, USA. Cognitive Neuropsychology, 26 (1), 36-49.

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Page 1: Grouping In Object Recognition

Grouping in object recognition: The role of a Gestalt law in letter identification

Pelli, Denis G., Majaj, Najib J., Raizman, Noah, Christian, Christopher J., Kim, Edward & Palomares, Melanie C. (2009).

Psychology and Neural Science, New York University, New York, NY, USA.

Cognitive Neuropsychology, 26 (1), 36-49.

Page 2: Grouping In Object Recognition

Gestalt Law

Grouping(proximity)

Most are binary discrimination tasks in the past

Page 3: Grouping In Object Recognition

Binary discrimination task

Differs from ordinary object recognition task

Quick Familiar Meaningful Named

Page 4: Grouping In Object Recognition

A well-known example from speech perception

• Hard task ABX (ABA or ABB)

• Simple task X (A or B)

The Difference on voice onset time in ABX task is much more noticeable

Page 5: Grouping In Object Recognition

• Simple X(A or B) task light memory load

• Hard ABX task higher memory load.

The simple one Less noticeableThe hard one more noticeable

Difference for voice onset time

Page 6: Grouping In Object Recognition

Grouping effects categorized object recognition

Page 7: Grouping In Object Recognition

To study object recognization

Study letter recognition

Identify snake letter

Page 8: Grouping In Object Recognition

Independent Variables : wiggle

Dependent Variables : Efficiency

based on the snake on the grass

Page 9: Grouping In Object Recognition

Wiggle The angle of sinusoid with the axis

Rotating Offsetting Phase shifting

Page 10: Grouping In Object Recognition

• To measure the relatively efficiency of recognition

• Use computer program to set an ideal observer ,as a reference for human performance on a absolute scale.

Geisler, 1989

Page 11: Grouping In Object Recognition

Measure the threshold contrast for 82% correct identification, both Human and Ideal observer.

• Compute contrast energy at threshold, integrated square of the contrast function

so the efficiency and energy are proportional to squared contrast

First proposed by Watson & Pelli, 1983

Page 12: Grouping In Object Recognition

Human observer

• Two undergraduate observer

• More data each observer

Use the concept akin to the method of psychophysics

Draw conclusion from individual, not averages

Page 13: Grouping In Object Recognition

Efficiency

To neglect Zero-noise threshold E0

Apply high background noise to elevate threshold E>>E0

E0 become relatively insignificant

Tanner, Birdsall(1958)

Pelli, Farell(1999)

Page 14: Grouping In Object Recognition
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Zero wiggle Efficiency = 8%

At wiggle higher than 15o Efficiency

Page 16: Grouping In Object Recognition

Conclusion

• Wiggle raises human threshold, not ideal observer

• Gestalt laws play an important role in letter identification, and may be an evidence of its importance at ordinary object recognition.

-END