Computer Vision - Important Concepts in Signal Processing, Image Processing and Data Compression - page 12

Object recognition : one or several pre-specified or learned objects or object
classes can be recognized, usually together with their 2D positions in the image or
3D poses in the scene.



Identification : An individual instance of an object is recognized. Examples:
identification of a specific person's face or fingerprint, or identification of a
specific vehicle.



Detection : the image data is scanned for a specific condition. Examples: detection
of possible abnormal cells or tissues in medical images or detection of a vehicle in
an automatic road toll system. Detection based on relatively simple and fast
computations is sometimes used for finding smaller regions of interesting image
data which can be further analysed by more computationally demanding
techniques to produce a correct interpretation.



Several specialized tasks based on recognition exist, such as:

Content-based image retrieval : finding all images in a larger set of images
which have a specific content. The content can be specified in different ways, for
example in terms of similarity relative a target image (give me all images similar
to image X), or in terms of high-level search criteria given as text input (give me
all images which contains many houses, are taken during winter, and have no cars
in them).



Pose estimation : estimating the position or orientation of a specific object
relative to the camera. An example application for this technique would be
assisting a robot arm in retrieving objects from a conveyor belt in an assembly
line situation.



Optical character recognition (OCR): identifying characters in images of
printed or handwritten text, usually with a view to encoding the text in a format
more amenable to editing or indexing (e.g. ASCII).



Motion analysis

Several tasks relate to motion estimation where an image sequence is processed to
produce an estimate of the velocity either at each points in the image or in the 3D scene,
or even of the camera that produces the images . Examples of such tasks are:

Egomotion : determining the 3D rigid motion (rotation and translation) of the
camera from an image sequence produced by the camera.



Tracking : following the movements of a (usually) smaller set of interest points or
objects (e.g., vehicles or humans) in the image sequence.



Optical flow : to determine, for each point in the image, how that point is moving
relative to the image plane, i.e., its apparent motion. This motion is a result both
of how the corresponding 3D point is moving in the scene and how the camera is
moving relative to the scene.



Scene reconstruction