PATENT CLAIM ANALYSIS

Application Number: 16003049
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-12
Patent Classification: ["725", "014000"]

Abstract:
The present disclosure provides a computer-implemented method and system for progressive penalty and reward based ad scoring for real time supervised detection of televised video ads in televised media content. The method includes reception of the media content and selection of a set of frames per second from the media content. The method includes extraction of key points from each selected frame and derivation of binary descriptors from extracted key points. The method includes assignment of weight value to each binary descriptor and creation of a special pyramid of the binary descriptors. The method includes obtaining a first vocabulary of binary descriptors for each selected frame and accessing a second vocabulary of binary descriptors. The method includes comparison of each binary descriptor in the first vocabulary with binary descriptors in second vocabulary. The method includes progressively scoring each selected frame of the media content for detection of a first ad.

Claim (Index 13):
A computer system comprising:\n one or more processors; and a memory coupled to the one or more processors, the memory for storing instructions which, when executed by the one or more processors, cause the one or more processors to perform a method for progressive penalty and reward based ad scoring for real time supervised detection of televised video ads in a live stream of a media content of a broadcasted channel, the method comprising: selecting, at an advertisement scoring system, a set of frames per second from a pre-defined set of frames in each second of the live stream of the media content; extracting, at the advertisement scoring system, a pre-defined number of key points from each selected frame of the media content; deriving, at the advertisement scoring system, a pre-defined number of binary descriptors from the corresponding pre-defined number of extracted key points, each binary descriptor being characterized by a binary string with a length of 256 bits; assigning, at the advertisement scoring system, a weight value to each binary descriptor of the pre-defined number of binary descriptors, wherein the weight value corresponding to each binary descriptor is L1 normalized and wherein each normalized weight value corresponding to each binary descriptor is characterized by an arithmetic sum of 1; creating, at the advertisement scoring system, a special pyramid of the pre-defined number of binary descriptors to obtain a pre-defined number of spatially identifiable binary descriptors, the special pyramid being created for obtaining a first vocabulary of binary descriptors corresponding to the pre-defined number of spatially identifiable binary descriptors of each selected frame; accessing, at the advertisement scoring system, a second vocabulary of binary descriptors corresponding to a curated comprehensive repository of ad frames from a comprehensive set of televised advertisements, wherein the second vocabulary comprises a set of tree structured clusters of binary descriptors; comparing, at the advertisement scoring system, each spatially identifiable binary descriptor from the pre-defined number of binary descriptors corresponding to the first vocabulary of each selected frame with a plurality of spatially identifiable binary descriptors in at least one or more clusters of the set of tree structured clusters corresponding to the second vocabulary of the binary descriptors of the repository of the ad frames, wherein each spatially identifiable binary descriptor in the first vocabulary of each selected frame is compared with the plurality of spatially identifiable binary descriptors in the second vocabulary for obtaining a summed feature value for each selected frame of the pre-defined set of frames; and progressively scoring, at the advertisement scoring system, each selected frame from the live stream of the media content for validation of the selected frame as the ad frame of a first ad, wherein the first ad is progressively scored for each positively validated frame to obtain a progressive ad score, the progressive score for each ad being calculated in at least one or more steps, wherein the one or more steps comprises: comparing the summed feature value for each selected frame with a first threshold value for validating the selected frame as the ad frame; evaluating a ratio test for determining degree of difference between each selected frame in the selected set of frames in the live stream of the media content, wherein the ratio test is evaluated by dividing the summed feature value for a second frame by the corresponding summed feature value for a first frame in the selected set of frames; rewarding a first ad of one or more ads in the live stream of the media content by assigning a first ad score for a positive validation of the evaluated ratio, wherein the first ad score is assigned to the first ad when the ratio is less than a second threshold value; penalizing a second ad of the one or more ads in the live stream of the media content by deducting a second score from the assigned first ad score for the second ad, wherein the second ad is a past ad streamed before the first ad and wherein the first ad is streamed in real time in the live stream of the media content; rewarding the first ad of the one or more ads in the live stream of the media content by adding a third score to the first ad score of the first ad, wherein the third score is rewarded based on an equality criterion and wherein the equality criterion is based on equality of the feature value of the first frame and the feature value of the second frame in the selected set of frames; rewarding the first ad of the one or more ads in the live stream of the media content by adding a fourth score to the first ad score of the first ad, wherein the fourth score is rewarded based on a vicinity criterion and wherein the vicinity criterion is based on successive positive validation of the selected set of frames; and calculating the progressive ad score for the first ad and the second ad based on at least one of progressive addition and subtraction of the second score, the third score and the fourth score to the first ad score.

Metadata:
- Claim Count in Document: 47.0
- Percentile: 94.0
- Lexical Diversity: 2.53226
- Patent Class: 725.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['13132597', '12841078', '14414048', '13041457', '14903590']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3834650857544659
- 35 USC 102 Novelty (BERT): 0.4940795150561169
- Combined Prediction Score: 0.394526528684631
- Mean Citation Score: 190.335102
- Max Citation Score: 210.71948
- Similarity Product: 152.9366897008133

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test