Abstract: Disclosed are a method and apparatus for determining a given template of a form used by a filled in instance of that type of form from amongst a great number of form templates (a hundred or more). The given instance is evaluated by a neural network that has been trained by a single example of each template in order to reduce the total number of templates down to a manageable amount. Given a list of closest matching templates, the instance is aligned to each of the closest matching templates. The comparison generates a match score. The form template having the greatest match score is the correct form template. Filtering the instance through a one-shot learning neural network before performing a precise comparison enables the process to scale to any number of template forms.

Abstract: Disclosed are a method and apparatus for determining a given variation of a form used by a filled in instance of that type of form from amongst a number of form templates. The given instance is aligned to each of the variants or form templates. The result of the alignment includes a series of key points that did not match up well (“bad” key points). The bad key points are taken from the form templates. Then, a set of pixel patches from around each of the bad key points of the form templates are extracted. The pixel patches are individually compared to corresponding pixel patches of the instance. The comparison generates a match score. The form template having the greatest match score is the correct form template.

Abstract: Disclosed are a method and apparatus for determining a given variation of a form used by a filled in instance of that type of form from amongst a number of form templates. The given instance is aligned to each of the variants or form templates. The result of the alignment includes a series of key points that did not match up well (“bad” key points). The bad key points are taken from the form templates. Then, a set of pixel patches from around each of the bad key points of the form templates are extracted. The pixel patches are individually compared to corresponding pixel patches of the instance. The comparison generates a match score. The form template having the greatest match score is the correct form template.

Abstract: A method for video sequential alignment is provided. The method includes inputting a first video sequence and a second video sequence, and extracting features of the first video sequence and the second video sequence. The method also includes generating an expanded path using a hierarchical sequential alignment algorithm and generating masks containing search space using keyframe matching. Further, the method includes calculating the lowest path cost within search space to find a minimal alignment path using a block A* algorithm and outputting a final alignment result after applying the block A* algorithm to search space.

Abstract: A method for video sequential alignment is provided. The method includes inputting a first video sequence and a second video sequence, and extracting features of the first video sequence and the second video sequence. The method also includes generating an expanded path using a hierarchical sequential alignment algorithm and generating masks containing search space using keyframe matching. Further, the method includes calculating the lowest path cost within search space to find a minimal alignment path using a block A* algorithm and outputting a final alignment result after applying the block A* algorithm to search space.