Animat Vision: Active Vision in Artificial Animals - PowerPoint PPT Presentation

Loading...

PPT – Animat Vision: Active Vision in Artificial Animals PowerPoint presentation | free to download - id: 6d7209-ZjczM



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Animat Vision: Active Vision in Artificial Animals

Description:

Animat Vision: Active Vision in Artificial Animals by Demetri Terzopoulos and Tamer F. Rabie Animat Vision What s an animat? - computational models of real animals ... – PowerPoint PPT presentation

Number of Views:5
Avg rating:3.0/5.0
Date added: 8 June 2020
Slides: 23
Provided by: Academ136
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Animat Vision: Active Vision in Artificial Animals


1
Animat Vision Active Vision in Artificial
Animals
  • by Demetri Terzopoulosand Tamer F. Rabie

2
Animat Vision
  • Whats an animat? - computational models of real
    animals situated in their natural habitats
  • Animate vision - a paradigm which prescribes the
    use of artificial animals as autonomous virtual
    robots for active vision research

3
Fish Animat
  • Challenge - to synthesize an active vision system
    for the fish animat, based solely on virtual
    retinal image analysis.
  • Binocular perspective projection of the 3D world
    onto the animats 2D retinas.
  • Use fish because they have simple goals, can swim
    in environment, rely on vision and recognition.

4
Hardware vs. Software Approach
  • Hardware approach
  • - Cant model the complexity of natural animals
  • - Expensive
  • Software approach
  • - Can slow down the cosmic clock
  • - The quantitative photometric, geometric, and
    dynamic information needed to render the virtual
    world is available explicitly

5
Previous Related Work
  • A point marker on a 2D grid world
  • 2D cockroaches
  • Kinematic dog
  • Animats using perceptual oracles

6
Qualities of Fish Animat
  • Motor system
  • Perception system
  • Behavior system
  • Form and Appearance

7
Motor System
  • Comprises the fish biomechanical model, including
    muscle actuators and a set of motor controllers
    (MCs)

8
Perception System
  • Model limitations as well as abilities
  • Perceptual attention mechanism - allows animat to
    act in a task-specific way
  • Perceptual oracles vs. animat vision

9
Behavior System
  • Mediates between the perception system and the
    motor system of the fish

10
Form and Appearance
11
Eyes and Retinal Imaging
12
Active Vision System
  • Must stabilize in environment
  • Must foveate on target

13
Locating a Target
  • Use Color Histogram Intersection
  • Most obvious algorithm is to compare the color
    distribution of the target with color
    distributions found on the retinal image

14
Problem with obvious solution
  • Only works if scale of target is similar to the
    scale of the image.
  • Works poorly if object is far away
  • Works poorly if object is semi-occluded.

15
Locating Targets Second Try
  • Iterate over scaled versions of the image and
    take the average.
  • Good Generally converges after 2-4 iterations.
  • Bad Leads to false alarms if model is overly
    scaled.

16
Locating Targets Third Try
  • Like before, but use a weighted average to place
    more importance on colors that are specific to
    the model.
  • In their experiments, usually converged to Pgt0.8
    or Plt0.2 within a few iterations.

17
Navigation
  • Once targets are located and can be tracked,
    navigation is trivial.
  • When left-right vision angles deviate by more
    than 30 degrees from center, tell body to turn
    left/right.
  • When up-down vision angles deviate by more than 5
    degrees, tell body to push up/down.

18
Pursuing Targets in Motion
  • How does this fish perform in pursuit of another
    virtual fish?
  • Ran an experiment and plotted gaze angles.
  • Performed well, was not distracted by fake
    targets.

19
Plot of Pursuit
20
Picture from Pursuit 1/2
21
Picture from Pursuit 2/2
22
Conclusions, Looking Forward...
  • Achieved goal of implementing a software-based
    artificial life simulation.
  • In the future, would like to develop a better
    active vision algorithm more suited to real fish.
  • Model can be made realistic enough to use
    resulting data to form theories about animals and
    robotic situated agents.
About PowerShow.com