PATENT CLAIM ANALYSIS

Application Number: 15888044
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-08
Patent Classification: ["348", "172000"]

Abstract:
The present invention is to provide a method and system using compressed data directly for target tracking and target classification in videos. The present invention uses a video imager to generate compressive measurements, and a random subsampling operator to compress the video data. It uses a Gaussian Mixture Model (GMM) for target detection and manual location of the target and putting a bounding box around the targets in the first frame is not required. It further applies a saliency-based algorithm to re-center the captured target. This re-centering process can be repeated multiple times and each application of re-centering will improve over the previous one. A pixel completion algorithm is used to fill in the missing pixels for the captured target area. A Sparse Representation Classification (SRC) for target classification. Both the target templates in a dictionary and captured targets are transformed to the frequency domain using Fast Fourier Transform (FFT).

Claim (Index 10):
A method of target detection, tracking and classification directly in a compressive measurement domain in accordance to  claim 6 , further comprising the steps of:\n transforming target templates in a dictionary and the detected targets to a frequency domain using Fast Fourier Transform (FFT).

Metadata:
- Claim Count in Document: 13.0
- Percentile: 88.0
- Lexical Diversity: 1.70103
- Patent Class: 348.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15088431', '12740947', '12091340', '14050296', '12091069']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5314089056776123
- 35 USC 102 Novelty (BERT): 0.4904242339156445
- Combined Prediction Score: 0.5273104385014156
- Mean Citation Score: 129.0808098
- Max Citation Score: 139.72116
- Similarity Product: 88.26625108040571

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

Dataset: test