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Object recognition (cognitive science)

Object recognition (cognitive science) is a biology topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Object recognition (cognitive science) rather than just read about it. In short: Visual object recognition refers to the cognitive ability to identify objects from visual perception. One important signature of visual object recognition is "object invariance", or the ability to identify objects across changes in the detailed context in which objects are viewed, including changes in illumination, object pose, and background context.

Object recognition (cognitive science) — main illustration
Object recognition (cognitive science) — illustration

Key takeaways

  • Object recognition (cognitive science) belongs to biology; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Object recognition (cognitive science) to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Object recognition (cognitive science) from memory before moving on to harder problems.

Reference excerpt

Visual object recognition refers to the cognitive ability to identify objects from visual perception. One important signature of visual object recognition is "object invariance", or the ability to identify objects across changes in the detailed context in which objects are viewed, including changes in illumination, object pose, and background context.

Basic stages of object recognition Neuropsychological evidence affirms that there are four specific stages identified in the process of object recognition. These stages are:

Processing of basic object components, such as color, depth, and form. These basic components are then grouped on the basis of similarity, providing information on distinct edges to the visual form. Subsequently, figure-ground segregation is able to take place. The visual representation is matched with structural descriptions in memory. Semantic attributes are applied to the visual representation, providing meaning, and thereby recognition. Within these stages, there are more specific processes that take place to complete the different processing components. In addition, other existing models have proposed integrative hierarchies (top-down and bottom-up), as well as parallel processing, as opposed to this general bottom-up hierarchy.

Hierarchical recognition processing Visual recognition processing is typically viewed as a bottom-up hierarchy in which information is processed sequentially with increasing complexities. During this process, lower-level cortical processors, such as the primary visual cortex, are at the bottom of the hierarchy. Higher-level cortical processors, such as the inferotemporal cortex (IT), are at the top, where visual recognition is facilitated. A highly recognized bottom-up hierarchical theory is James DiCarlo's Untangling description whereby each stage of the hierarchically arranged ventral visual pathway performs operations to gradually transform object representations into an easily extractable format. In contrast, an increasingly popular recognition processing theory, is that of top-down processing. One model, proposed by Moshe Bar (2003), describes a "shortcut" method in which early visual inputs are sent, partially analyzed, from the early visual cortex to the prefrontal cortex (PFC). Possible interpretations of the crude visual input is generated in the PFC and then sent to the inferotemporal cortex (IT) subsequently activating relevant object representations which are then incorporated into the slower, bottom-up process. This "shortcut" is meant to minimize the number of object representations required for matching thereby facilitating object recognition. Lesion studies have supported this proposal with findings of slower response times for individuals with PFC lesions, suggesting use of only the bottom-up processing.

Object constancy and theories of object recognition

A significant aspect of object recognition is that of object constancy: the ability to recognize an object across varying viewing conditions. These varying conditions include object orientation, lighting, and object variability (size, color, and other within-category differences). For the visual system to achieve object constancy, it must be able to extract a commonality in the object description across different viewpoints and the retinal descriptions.[9] Participants who did categorization and recognition tasks while undergoing a functional magnetic found as increased blood flow indicating activation in specific regions of the brain. The categorization task consisted of participants placing objects from canonical or unusual views as either indoor or outdoor objects. The recognition task occurs by presenting the participants with images that they had viewed previously. Half of these images were in the same orientation as previously shown, while the other half were presented in the opposing viewpoint. The brain regions implicated in mental rotation, such as the ventral and dorsal visual pathways and the prefrontal cortex, showed the greatest increase in blood flow during these tasks, demonstrating that they are critical for the ability to view objects from multiple angles. Several theories have been generated to provide insight on how object constancy may be achieved for the purpose of object recognition including, viewpoint-invariant, viewpoint-dependent and multiple views theories.

Viewpoint-invariant theories Viewpoint-invariant theories suggest that object recognition is based on structural information, such as individual parts, allowing for recognition to take place regardless of the object's viewpoint. Accordingly, recognition is possible from any viewpoint as individual parts of an object can be rotated to fit any particular view.[10] This form of analytical recognition requires little memory as only structural parts need to be encoded, which can produce multiple object representations through the interrelations of these parts and mental rotation.[10] Participants in a study were presented with one encoding view from each of 24 preselected objects, as well as five filler images. Objects were then represented in the central visual field at either the same orientation or a different orientation than the original image. Then participants were asked to name if the same or different depth- orientation views of these objects presented. The same procedure was then executed when presenting the images to the left or right visual field. Viewpoint-dependent priming was observed when test views were presented directly to the right hemisphere, but not when test views were presented directly to the left hemisphere. The results support the model that objects are stored in a manner that is viewpoint dependent because the results did not depend on whether the same or a different set of parts could be recovered from the different-orientation views.

… excerpt ends here. Continue reading the full article.

Illustrations

Object recognition (cognitive science) illustration
Object recognition (cognitive science): Figure 1. This image, created based on Biederman's (1987) Recognition by Components theory, is an example of how objects can be broken down into Geons.
Figure 1. This image, created based on Biederman's (1987) Recognition by Components theory, is an example of how objects can be broken down into Geons.
Object recognition (cognitive science): The Dorsal Stream is shown in green and the Ventral Stream in purple.
The Dorsal Stream is shown in green and the Ventral Stream in purple.

Worked examples

Example 1 — a first encounter with Object recognition (cognitive science)

Start with the simplest possible case. Write down what Object recognition (cognitive science) claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In biology, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Object recognition (cognitive science) before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Object recognition (cognitive science) ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Object recognition (cognitive science)

In research
Object recognition (cognitive science) appears in biology research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Object recognition (cognitive science) in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Object recognition (cognitive science) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cognitive neuroscience, so understanding it makes those chapters shorter.
In everyday life
Look for Object recognition (cognitive science) outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Object recognition (cognitive science) in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Object recognition (cognitive science) means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Object recognition (cognitive science) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Object recognition (cognitive science) in simple terms?

Visual object recognition refers to the cognitive ability to identify objects from visual perception. One important signature of visual object recognition is "object invariance", or the ability to identify objects across changes in the detailed context in which objects are viewed, including changes…

Why does Object recognition (cognitive science) matter?

Because it connects several biology ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Object recognition (cognitive science)?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Object recognition (cognitive science).

Tags

  • Cognitive neuroscience

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