Abstract: Methods and apparatus to improve detection and false alarm rate over image segmentation are disclosed. An example method includes determining a first score based on a first pixel distance between a first feature of a first object in a reference image and a second feature in a second image of a search area, determining a second score corresponding to a second pixel distance between the second feature and a mathematical representation of a plurality of shapes representing a similarity between the second feature in the second image of the search area and the plurality of shapes observed simultaneously. The method further includes determining a normalized score by normalizing the first score based on the second score and identifying a second object in the second image of the search area as the first object in the reference image when the normalized score satisfies a threshold score.

Abstract: Methods and apparatus to improve detection and false alarm rate over image segmentation are disclosed. An example method includes determining a first score based on a first pixel distance between a first feature of a first object in a reference image and a second feature in a second image of a search area, determining a second score corresponding to a second pixel distance between the second feature and a mathematical representation of a plurality of shapes representing a similarity between the second feature in the second image of the search area and the plurality of shapes observed simultaneously. The method further includes determining a normalized score by normalizing the first score based on the second score and identifying a second object in the second image of the search area as the first object in the reference image when the normalized score satisfies a threshold score.

Abstract: Example methods, apparatus, systems to perform context-based image recognition are disclosed. Disclosed example methods include comparing a first and second reference region of a reference image with a first and second region of a first captured image to determine a first and second match value. In response to determining the first and second match values satisfy a first and second threshold: associating the first captured image with a product associated with the first reference image, the product being associated with a plurality of second reference images stored in the database. Decrementing index values associated with ones of the second reference images. Removing a reference record associated with one of the second reference images from the database based on a corresponding one of the second index values satisfying a first condition, the removal of the reference record reducing the storage space required to store reference records in the database.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed herein. An example method to improve object detection and false alarm rate over image segmentation includes overlaying a first object of a first image onto a second image. A first score based on a first chamfer distance between first edges of the first object and second edges in the second image is determined. A second score corresponding to a second chamfer distance between the second edges and a mathematical representation of a plurality of shapes is determined, the second score representing a similarity between the second edges and the plurality of shapes observed simultaneously. A normalized score is determined by normalizing the first score based on the second score. A presence of the second object in the second image matching the first object is detected based on whether the normalized score satisfies a threshold score.

Abstract: Example methods, apparatus, systems to perform context-based image recognition are disclosed. Disclosed example methods include comparing a first and second reference region of a reference image with a first and second region of a first captured image to determine a first and second match value. In response to determining the first and second match values satisfy a first and second threshold: associating the first captured image with a product associated with the first reference image, the product being associated with a plurality of second reference images stored in the database. Decrementing index values associated with ones of the second reference images. Removing a reference record associated with one of the second reference images from the database based on a corresponding one of the second index values satisfying a first condition, the removal of the reference record reducing the storage space required to store reference records in the database.

Abstract: Example methods, apparatus, systems to perform context-based image recognition for consumer market research are disclosed. Disclosed example methods include comparing a first subset of feature points in a first region of interest of a reference image with a first subset of feature points of a first image residing within a first region corresponding spatially to the first region of interest and located at a first location in the first image to determine a first match value. Disclosed example methods also include, in response to determining the first match value satisfies a first threshold, comparing a second subset of feature points in a second region of interest of the reference image with a second subset of the feature points of the first image residing within a second region of the first image corresponding spatially to the second region of interest to determine a second match value.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed herein. An example method to improve object detection and false alarm rate over image segmentation includes overlaying a first object of a first image onto a second image. A first score based on a first chamfer distance between first edges of the first object and second edges in the second image is determined. A second score corresponding to a second chamfer distance between the second edges and a mathematical representation of a plurality of shapes is determined, the second score representing a similarity between the second edges and the plurality of shapes observed simultaneously. A normalized score is determined by normalizing the first score based on the second score. A presence of the second object in the second image matching the first object is detected based on whether the normalized score satisfies a threshold score.

Abstract: Example methods, apparatus, systems to perform context-based image recognition for consumer market research are disclosed. Disclosed example methods include comparing a first subset of feature points in a first region of interest of a reference image with a first subset of feature points of a first image residing within a first region corresponding spatially to the first region of interest and located at a first location in the first image to determine a first match value. Disclosed example methods also include, in response to determining the first match value satisfies a first threshold, comparing a second subset of feature points in a second region of interest of the reference image with a second subset of the feature points of the first image residing within a second region of the first image corresponding spatially to the second region of interest to determine a second match value.