Abstract: A digital image of a first garment having one or more first garment portions is received. A user has identified the first garment portions as matching one or more corresponding second garment portions of a second garment. The probability of accidental match of the first garment within the digital image in relation to the second garment is determined, by using a statistical model based on one or more parameters and based on analyses of the first garment portions. The probability of accidental match is output.

Abstract: Visual odometry is achieved via various approaches.

Abstract: A digital image of a first garment having one or more first garment portions is received. A user has identified the first garment portions as matching one or more corresponding second garment portions of a second garment. The probability of accidental match of the first garment within the digital image in relation to the second garment is determined, by using a statistical model based on one or more parameters and based on analysis of the first garment portions. The probability of accidental match is output.

Abstract: Dot templates are used for detecting objects within images. A computer-implemented method is performed for each of a number of dot templates corresponding to the object to be detected within an image. Each dot template is defined as a collection of points. At each position within the image, a value of the image is determined at each point of the dot template. The dot template is effectively overlaid at the given position within the image. A score of the dot template at this position is determined, based on the values of the image determined at the points of the dot template. Where the score is greater than a predetermined threshold, it can be concluded that the object is at least potentially located within the image at the position in question at which the dot template has been effectively overlaid.

Abstract: Dot templates are used for detecting objects within images. A computer-implemented method is performed for each of a number of dot templates corresponding to the object to be detected within an image. Each dot template is defined as a collection of points. At each position within the image, a value of the image is determined at each point of the dot template. The dot template is effectively overlaid at the given position within the image. A score of the dot template at this position is determined, based on the values of the image determined at the points of the dot template. Where the score is greater than a predetermined threshold, it can be concluded that the object is at least potentially located within the image at the position in question at which the dot template has been effectively overlaid.

Abstract: A digital image of a first garment having one or more first garment portions is received. A user has identified the first garment portions as matching one or more corresponding second garment portions of a second garment. The probability of accidental match of the first garment within the digital image in relation to the second garment is determined, by using a statistical model based on one or more parameters and based on analyses of the first garment portions. The probability of accidental match is output.

Abstract: Dot templates are used for detecting objects within images. A computer-implemented method is performed for each of a number of dot templates corresponding to the object to be detected within an image. Each dot template is defined as a collection of points. At each position within the image, a value of the image is determined at each point of the dot template. The dot template is effectively overlaid at the given position within the image. A score of the dot template at this position is determined, based on the values of the image determined at the points of the dot template. Where the score is greater than a predetermined threshold, it can be concluded that the object is at least potentially located within the image at the position in question at which the dot template has been effectively overlaid.

Abstract: Dot templates are used for detecting objects within images. A computer-implemented method is performed for each of a number of dot templates corresponding to the object to be detected within an image. Each dot template is defined as a collection of points. At each position within the image, a value of the image is determined at each point of the dot template. The dot template is effectively overlaid at the given position within the image. A score of the dot template at this position is determined, based on the values of the image determined at the points of the dot template. Where the score is greater than a predetermined threshold, it can be concluded that the object is at least potentially located within the image at the position in question at which the dot template has been effectively overlaid.

Abstract: Dot templates are used for detecting objects within images. A computer-implemented method is performed for each of a number of dot templates corresponding to the object to be detected within an image. Each dot template is defined as a collection of points. At each position within the image, a value of the image is determined at each point of the dot template. The dot template is effectively overlaid at the given position within the image. A score of the dot template at this position is determined, based on the values of the image determined at the points of the dot template. Where the score is greater than a predetermined threshold, it can be concluded that the object is at least potentially located within the image at the position in question at which the dot template has been effectively overlaid.

Abstract: Dot templates are used for detecting objects within images. A computer-implemented method is performed for each of a number of dot templates corresponding to the object to be detected within an image. Each dot template is defined as a collection of points. At each position within the image, a value of the image is determined at each point of the dot template. The dot template is effectively overlaid at the given position within the image. A score of the dot template at this position is determined, based on the values of the image determined at the points of the dot template. Where the score is greater than a predetermined threshold, it can be concluded that the object is at least potentially located within the image at the position in question at which the dot template has been effectively overlaid.