w9 gemini Flashcards
What is the topic of today’s lecture, according to slide 1?
Object recognition
What are the three levels of computer vision discussed in the recap on slide 1?
Low-level vision, Mid-level vision, High-level vision
Name four topics covered under Mid-level vision in the recap (slide 1).
Segmentation and grouping, Correspondence problem, Stereo and Depth, Video and Motion
What are the three main aspects of object recognition, as defined on slide 2?
Identification, Categorisation, Localisation
Give three examples of methods for performing object recognition (slide 2).
Template matching, Sliding window, Edge matching
What is the goal of object identification, according to slide 3?
To determine the identity of an individual instance of an object.
Give an example of object identification from slide 3.
Distinguishing between two specific individuals (Clinton vs. Bush) or two specific phone models (Samsung Galaxy On8 vs. iPhone 7 Plus).
What is the goal of object categorisation, as described on slide 4?
To determine the category of an object.
Provide an example of object categorisation from slide 4.
Classifying images as belonging to the category ‘Human’ or ‘Chimpanzee’, or ‘Telephone’ or ‘Calculator’.
What is object localisation, according to slide 5?
Determining the presence and/or location of an object in an image.
What is semantic segmentation, as defined on slide 6?
Localisation that is sufficiently fine-grained and for a sufficiently large number of categories, resulting in image segmentation.
Explain the concept of a category hierarchy in object recognition (slide 7).
Classification can occur at different levels of abstraction, from general categories (like ‘object’) to specific instances (like ‘Rex’).
What are the three levels in the category hierarchy shown on slide 7?
Superordinate level, Basic level, Subordinate level
Why is the ‘basic level’ significant for human object recognition (slide 8)?
Humans are usually fastest at recognizing category members at this level, start with basic-level categorization before identification, and it’s the first level understood by children.
List two reasons why the basic level is considered special (slide 9).
It’s the highest level where category members share many common features, and the lowest level where members have features distinct from other categories at the same level.
What are the two main requirements for object recognition systems (slide 10)?
Sensitivity to image differences relevant to distinguishing objects, and insensitivity/tolerance to differences that don’t affect object identity or category.
Give examples of image variations that object recognition systems should be insensitive to (slides 11-13).
Background clutter, occlusion, viewpoint, lighting, non-rigid deformations, within-category variation.
What are the three main components required for object recognition (slide 14)?
Image data, representations of objects, matching techniques.
Describe the ‘off-line’ stage of object recognition procedure (slide 15).
Extracting representations from training examples.
Describe the ‘on-line’ stage of object recognition procedure (slide 15).
Extracting representation from an input image and matching it with training examples to determine the object class or identity.
What are the two key aspects in which object recognition methods vary (slide 16)?
Representation used and matching procedure.
What is the representation used in template matching (slide 17)?
An image of the object to be recognized (an array of pixel intensities).
Describe the matching process in template matching (slide 17).
Searching every image region and calculating the similarity between the template and the image region.
Name three similarity measures that can be maximised in template matching (slide 18).
Cross-correlation, Normalised cross-correlation (NCC), Correlation coefficient.