1 Perception and VR MONT 104S, Fall 2008 Lecture 6 Seeing Motion.

Slides:



Advertisements
Similar presentations
Chapter 4: The Visual Cortex and Beyond
Advertisements

The Primary Visual Cortex
Chapter 3: Neural Processing and Perception. Lateral Inhibition and Perception Experiments with eye of Limulus –Ommatidia allow recordings from a single.
The Central Visual System
Perception Chapter 9: Event Perception Event Perception: an event is defined as a change in both time and space. Thus far we have discussed how our visual.
MOTION PERCEPTION Types of Motion Perception Corollary Discharge Theory Movement Detectors Motion Perception and Object Perception Ecological Perception.
Chapter 6 Spatial Vision. The visual system recognizes objects from patterns of light and dark. We will focus on the mechanisms the visual system uses.
What is vision Aristotle - vision is knowing what is where by looking.
M OTION P ERCEPTION Michelle Vasquez. M OTION Defintion: change in an object’s location over time First order motion: change in luminance Second order.
Imaging Science FundamentalsChester F. Carlson Center for Imaging Science The Human Visual System Part 2: Perception.
1 Computational Vision CSCI 363, Fall 2012 Lecture 35 Perceptual Organization II.
Perception Chapter 3 Light is necessary but not sufficient for vision Ganzfeld: a visual field completely lacking in contour, or luminance changes. Prolonged.
1 Computational Vision CSCI 363, Fall 2012 Lecture 33 Color.
Higher Processing of Visual Information: Lecture III
How does the visual system represent visual information? How does the visual system represent features of scenes? Vision is analytical - the system breaks.
Imaging Science FundamentalsChester F. Carlson Center for Imaging Science Binocular Vision and The Perception of Depth.
Visual Cognition I basic processes. What is perception good for? We often receive incomplete information through our senses. Information can be highly.
The Human Visual System Vonikakis Vasilios, Antonios Gasteratos Democritus University of Thrace
Visual motion Many slides adapted from S. Seitz, R. Szeliski, M. Pollefeys.
PY202 Overview. Meta issue How do we internalise the world to enable recognition judgements to be made, visual thinking, and actions to be executed.
Computational Architectures in Biological Vision, USC, Spring 2001
Basic Processes in Visual Perception
The visual system Lecture 1: Structure of the eye
Laurent Itti: CS599 – Computational Architectures in Biological Vision, USC Lecture 5: Introduction to Vision 2 1 Computational Architectures in.
Beyond the Striate Cortex. Extrastriate Pathways  Parallel processing of visual information from the striate cortex.  Three pathways: Color processing.
University Studies 15A: Consciousness I The Neurobiology of Vision.
1B50 – Percepts and Concepts Daniel J Hulme. Outline Cognitive Vision –Why do we want computers to see? –Why can’t computers see? –Introducing percepts.
Another viewpoint: V1 cells are spatial frequency filters
1 Computational Vision CSCI 363, Fall 2012 Lecture 26 Review for Exam 2.
1 Perception and VR MONT 104S, Fall 2008 Lecture 7 Seeing Color.
Active Vision Key points: Acting to obtain information Eye movements Depth from motion parallax Extracting motion information from a spatio-temporal pattern.
1 Computational Vision CSCI 363, Fall 2012 Lecture 3 Neurons Central Visual Pathways See Reading Assignment on "Assignments page"
Psychology 4051 The Retina and LGN. Retino-Geniculate-Cortical Pathway.
1 Perception, Illusion and VR HNRS , Spring 2008 Lecture 3 The Eye.
1 Computational Vision CSCI 363, Fall 2012 Lecture 31 Heading Models.
THE VISUAL SYSTEM: EYE TO CORTEX Outline 1. The Eyes a. Structure b. Accommodation c. Binocular Disparity 2. The Retina a. Structure b. Completion c. Cone.
1 Computational Vision CSCI 363, Fall 2012 Lecture 20 Stereo, Motion.
1 Perception, Illusion and VR HNRS 299, Spring 2008 Lecture 8 Seeing Depth.
1 Perception, Illusion and VR HNRS 299, Spring 2008 Lecture 2 Introduction, Light Course webpage:
Chapter 8: Perceiving Motion
1 Computational Vision CSCI 363, Fall 2012 Lecture 28 Structure from motion.
Chapter 3: Neural Processing and Perception. Neural Processing and Perception Neural processing is the interaction of signals in many neurons.
1 Computational Vision CSCI 363, Fall 2012 Lecture 21 Motion II.
1 Computational Vision CSCI 363, Fall 2012 Lecture 5 The Retina.
3D Imaging Motion.
Vision Photoreceptor cells Rod & Cone cells Bipolar Cells Connect in between Ganglion Cells Go to the brain.
1 Perception and VR MONT 104S, Fall 2008 Lecture 4 Lightness, Brightness and Edges.
1 Computational Vision CSCI 363, Fall 2012 Lecture 24 Computing Motion.
Mind, Brain & Behavior Wednesday February 19, 2003.
1 Perception and VR MONT 104S, Fall 2008 Lecture 2 The Eye.
Higher Visual Areas 1.Anatomy of higher visual areas 2.Two processing pathways - “ Where ” pathway for motion and depth - “ What ” pathway for form and.
Visual Perception and Illusions. Optical Illusions Which of the above gray rectangles is darker?
Computational Vision CSCI 363, Fall 2012 Lecture 22 Motion III
Perception and VR MONT 104S, Fall 2008 Lecture 8 Seeing Depth
Week 4 Motion, Depth, Form: Cormack Wolfe Ch 6, 8 Kandell Ch 27, 28 Advanced readings: Werner and Chalupa Chs 49, 54, 57.
1 Computational Vision CSCI 363, Fall 2012 Lecture 16 Stereopsis.
Sensation & Perception. Motion Vision I: Basic Motion Vision.
Gestalt Principles of Perception Psychology 355: Cognitive Psychology Instructor: John Miyamoto 04/08 /2015: Lecture 02-3 This Powerpoint presentation.
Understanding Psychophysics: Spatial Frequency & Contrast
How we actively interpret our environment..  Perception: The process in which we understand sensory information.  Illusions are powerful examples of.
1 Computational Vision CSCI 363, Fall 2012 Lecture 29 Structure from motion, Heading.
1 Computational Vision CSCI 363, Fall 2012 Lecture 2 Introduction to Vision Science.
1 Computational Vision CSCI 363, Fall 2012 Lecture 32 Biological Heading, Color.
1 Perception and VR MONT 104S, Spring 2008 Lecture 3 Central Visual Pathways.
Psychology 304: Brain and Behaviour Lecture 28
2D Motion is just the Beginning
Early Processing in Biological Vision
Optic Nerve Projections
Measuring motion in biological vision systems
Neural Mechanisms of Visual Motion Perception in Primates
Presentation transcript:

1 Perception and VR MONT 104S, Fall 2008 Lecture 6 Seeing Motion

2 Tips for Scientific Writing 1.Stay focused: Writing should address question. Good: People in the distance appeared to be small. Their size helped me to judge their distance. Not-so-good: The scenery was spectacular. The lakes were small so I could not see any details. 2.Provide specific examples as evidence. 3.Write it all out: Good: When walking downhill, things that were more distant were lower in the visual field. This is a situation in which height in the visual field would not be a useful cue to distance. Not-so-good: I misjudged the size of the rocks. 4.Answer each part of the question: When size works, when size doesn't work, when height works, when height doesn't work. 5.Be as clear as you can be. Simple and clear is better than flowery and obtuse.

3 Causes of Image Motion Image motion can result from numerous causes: A moving object in the scene Eye movements Motion of the observer

4 Uses of Image Motion Image motion on the retina can be used to compute a variety of scene properties. Among them are: Image segmentation (dividing up the scene into individual objects or surfaces) 3D structure of an object (structure from motion) Depth (motion parallax) Time to collision Heading direction Moving object direction Speed of eye movements (for smooth pursuit)

5 Two stages of Motion processing Visual motion processing is thought to occur in two stages: 1)Extract the 2D image velocity field. 2)Use the 2D velocity field to compute properties of the scene (as listed in the previous slide).

6 Motion Detection by Neurons Problem: A single photoreceptor (or retinal ganglion cell) cannot detect motion unambiguously. A spot of light moving across its receptive field will cause a temporary increase in light followed by a decrease. The photoreceptor cannot distinguish between motion or changes in ambient lighting.

7 A Neural Circuit for Motion Barlow and Levick proposed a model to compare the response at one location with a delayed response at a neighboring position. Prefers right motion 1.Each neuron has a receptive field that is shifted to the left with respect to the receptive field of the previous neuron. 2.Each neuron causes the neuron with a RF to its left to be inhibited a short time after the first neuron is stimulated. 3.The neurons in the circuit will not respond to leftward motion because of this inhibition. 4.They will still respond to rightward motion.

8 Mapping of Visual Areas This map shows a flattened cortex with the known visual areas mapped onto it. There are a large number of distinct visual areas (probably at least 20). Each area appears to have a specific function. The areas show a roughly hierarchical organization (although most areas have reciprocal connections).

9 Two Major Processing Streams There appear to be 2 major processing streams (although there are cross connections between them): 1.The Dorsal Stream: Includes areas MT, MST, VIP, 7a, etc. Processes motion, stereo, spatial relationships The "where" pathway. 2.The Ventral Stream: Includes areas V4, IT, etc. Processes color, form, objects. The "what" pathway.

10 Dorsal and Ventral Streams

11 Motion Processing in V1 In V1, some simple cells and complex cells are tuned to direction of motion. I.e. they respond most strongly to motion in a given direction and their response falls off as the motion deviates from that direction. 180 o 120 o 240 o Firing Rate Direction of Motion Direction Tuning Polar Plot (tuning for zero deg) Tuning for 180 deg

12 Motion Processing in MT MT (The Middle Temporal Area) is thought to be important for processing motion information. Characteristics of MT neurons: 1)Cells tuned for direction of motion (more broadly tuned than V1 cells. 2)Cells tuned for speed. 3)Large receptive field sizes. (Some are 100x bigger than V1 receptive fields). They range from 1-2deg in diameter in the foveal region and increase in the periphery.

13 Speed Selectivity McKee and Nakayama have shown that people are very good at discriminating two different speeds. The Weber fraction gives a measure of how big a change in speed is necessary to distinguish two different speeds. It is fairly constant over a broad range of speeds:  V/V =.05 MT may be the area that first computes speed.

14 The Aperture Problem If our view is limited to an edge seen through an aperture, we can only find the component of motion perpendicular to the edge. The aperture problem is a fundamental problem when one is trying to measure image velocity using local detectors. This is true in biological vision (neurons have local receptive fields). In the "barber pole" illusion, the edges of the aperture affect perception. Aperture Edge Perpendicular velocity component

15 Motion Adaptation MT cells do not respond if opposite directions of motion (e.g. left and right) presented at the same time. This is called motion opponency. The detectors for opposite directions balance each other. The waterfall effect: If you view one direction of motion for a long time, the detectors for that direction become fatigued. If you then look at a stationary surface, it will appear to move in the opposite direction. This works for expansion and contraction as well. Demo:

16 2D Motion is just the Beginning 2D image motion contains information about: Relative depth of surfaces 3D motion of objects 3D structure of objects Direction of observer motion Among other things. Many of these tasks require local comparisons of neighboring motions.

17 Motion Parallax For an observer moving in a straight line, the images of objects that are nearby move faster than the images of objects that are far away. This is the result of perspective projection. The difference in image speed, known as motion parallax, is a strong cue for the relative depth of objects. A moving observer can find changes in depth in the scene by finding changes in image speed. object 1 object 2

18 MT cells have inhibitory surround + -Many MT cells have an inhibitory surround. Motion in the surround inhibits the response to motion in the center. The inhibitory surround may be involved in: Figure-ground segmentation based on motion. Motion parallax Heading judgments (judging where one is going).

19 Structure From Motion Relative motion can give information about the 3D structure of objects. Structure from motion originally studied rigorously by Wallach and O'Connell (1953). They studied wire-frame objects and examined peoples ability to judge the structure of the objects when moving. The ability to see a 3D structure from a moving 2D image is known as the Kinetic Depth Effect. Demo:

20 Detecting Biological Motion Johansson attached points of light to the joints of people and filmed them walking. He showed that when the lights are in motion, people can recognize the actions being performed. Demo: Relative motion of the points of light is certainly important for recognizing the actions.

21 Using Motion to See Where You're Going When one moves in a straight line, the images on the retina move in a radial pattern. The center of the pattern coincides with the direction you're going. When we move on a curved path, the computation is more difficult (and involves relative motion), but we can still judge our path of motion.