PATENT CLAIM ANALYSIS

Application Number: 15996078
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-12
Patent Classification: ["382", "103000"]

Abstract:
Methods and arrangements involving portable user devices such smartphones and wearable electronic devices are disclosed, as well as other devices and sensors distributed within an ambient environment. Some arrangements enable a user to perform an object recognition process in a computationally- and time-efficient manner. Other arrangements enable users and other entities to, either individually or cooperatively, register or enroll physical objects into one or more object registries on which an object recognition process can be performed. Still other arrangements enable users and other entities to, either individually or cooperatively, associate registered or enrolled objects with one or more items of metadata. A great variety of other features and arrangements are also detailed.

Claim (Index 10):
A method employing one or more computer processors to perform acts including:\n storing, within an object registry, model data and object metadata corresponding to a plurality of physical reference objects, the model data for each physical reference object including data characterizing plural non-coplanar surface regions of different extents and locations, and hybrid-P feature data, the model data also including, for each of several different physical reference objects, multiple sets of feature information, each set of feature information being associated with a particular viewpoint towards a physical reference object; obtaining query data representing a physical object-of-interest, wherein generation of the query data is initiated by a user, and said query data includes object profile data representing an edge of a silhouette of the physical object-of interest; performing an object recognition process on the query data, the object recognition process including processing the query data, in conjunction with the stored model data, to determine whether the object-of-interest corresponds to any of the plurality of physical reference objects, said object recognition process including identifying plural sets of said feature information that may correspond to the query data, thereby identifying a first candidate set of plural physical reference objects that possibly match said physical object-of-interest, and performing a clustering operation on viewpoints associated with said identified plural sets of feature information, to determine a preliminary candidate viewpoint towards a matching physical reference object; the object recognition process further including, for each of said first candidate set of physical reference objects, obtaining reference object profile data corresponding to said preliminary candidate viewpoint, and for one or more additional viewpoints; and performing a profile matching operation to identify certain of said obtained reference object profile data that correspond to the object profile data representing the physical object-of-interest, thereby identifying a second candidate set of physical reference objects that possibly match said physical object-of-interest, said second candidate set being smaller than said first candidate set; and upon determining that the object-of-interest corresponds to at least one of the physical reference objects, transmitting a result to a user device associated with the user, the result including object metadata associated with the at least one of the physical reference objects determined to correspond to the object-of-interest; wherein the hybrid-P feature data is based on an accumulation of multiple profiles of the reference object from multiple viewpoints.

Metadata:
- Claim Count in Document: 14.0
- Percentile: 94.0
- Lexical Diversity: 1.74286
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14251229', '15332262', '15050063', '15524944', '15350003']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3535105288365471
- 35 USC 102 Novelty (BERT): 0.4892178136065856
- Combined Prediction Score: 0.367081257313551
- Mean Citation Score: 207.734874
- Max Citation Score: 278.2503
- Similarity Product: 274.8536401375472

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

Dataset: test