PATENT CLAIM ANALYSIS

Application Number: 16228579
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-11
Patent Classification: ["382", "103000"]

Abstract:
A technique is disclosed for automating tracking of annotated objects and improves the throughput and efficiency of existing methods while maintaining a degree of accuracy comparable to a human annotator. In particular, the disclosed technique provides an automated annotated object tracking tool that allows machine-learning teams to annotate an object within a frame and have that annotation persist across frames as the annotated object is tracked within a series of frames, still ensuring that every frame is accurately reviewed by a human where high quality annotation is required. This technique incorporates human feedback via a user adjustment that allows the tool to adapt and improve its accuracy in tracking an annotated object across a sequence of frames.

Claim (Index 9):
The system of  claim 1  wherein the processor is further configured to predict the location of the object in the second frame including by applying a plurality of trackers, wherein the prediction is based at least in part by selecting an output from one of the plurality of trackers.

Metadata:
- Claim Count in Document: 11.0
- Percentile: 98.0
- Lexical Diversity: 1.71831
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15973114', '15645555', '15655065', '15965665', '15400118']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3414744020557412
- 35 USC 102 Novelty (BERT): 0.4813054080801226
- Combined Prediction Score: 0.3554575026581794
- Mean Citation Score: 165.607178
- Max Citation Score: 171.13779
- Similarity Product: 120.0601672573185

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

Dataset: test