Automated Token Detection in Video Sequences

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Solution Overview

Problem

The manual process of identifying and extracting information from tokens in video sequences during film production is time-consuming and cumbersome, requiring manual cueing and synchronization of audio-visual tracks.

Innovation Solution

A method for automatically detecting tokens in video sequences by scanning for boundaries, pre-selecting candidate regions, and using classifiers to identify and extract information, including the status of the slate arm, to synchronize audio and video tracks.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual slate identification is used, then flexibility and adaptability are maintained, but time consumption and labor effort increase significantly

Engineering Contradiction:

Improvemanual operation flexibilityVSAvoidtime consumption

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical operations (rewinding, cueing, visual inspection) with an automated computer-based system that processes video sequences algorithmically. The system automatically detects slate images, extracts information, and synchronizes audio-video tracks without human intervention, thereby eliminating time consumption while maintaining operational effectiveness

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system performs self-service by automatically detecting and processing slates within the video sequences. The algorithm independently identifies slate images, extracts text information, determines timing, and coordinates synchronization without requiring external manual input or human operators, thus resolving the time loss issue while preserving operational capability

Inventive Principle:

Principle #25Self-service

2Productivity

If automated token detection is implemented, then time consumption is reduced, but system complexity increases

Engineering Contradiction:

Improveprocessing speedVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments the complex task of automated slate detection into distinct manageable modules: video sequence processing, image extraction, slate image detection, information extraction, and synchronization. Each module handles a specific function independently, making the overall complex system modular and manageable while achieving high processing speed through automation

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces an intermediary processing layer between the raw video data and the final synchronization output. This intermediary layer includes image processing algorithms and data extraction modules that mediate between the complex video stream and the required synchronization information, enabling automated processing while managing system complexity through structured intermediate processing steps

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If manual information extraction is performed, then accuracy can be verified, but labor effort and time required increase

Engineering Contradiction:

Improveinformation extraction accuracyVSAvoidprocessing efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent substitutes manual information extraction with automated optical character recognition (OCR) algorithms and data parsing systems. These automated systems extract text information from slate images with high accuracy, maintaining verification capabilities through algorithmic validation while eliminating the labor effort and time consumption associated with manual extraction and entry

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Reliability

If comprehensive token detection is performed, then detection accuracy improves, but computational resources and processing time increase

Engineering Contradiction:

Improvedetection accuracyVSAvoidcomputational resource consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent applies local quality analysis by focusing computational resources on specific regions of interest within the video frames where slates are likely to appear. The system uses spatial filtering and region-based detection algorithms that concentrate processing power on relevant areas rather than analyzing the entire video stream uniformly, thereby maintaining high detection accuracy while reducing overall computational resource consumption

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system performs preliminary actions by pre-processing video frames to identify and isolate potential slate images before full analysis. This includes preliminary image extraction, basic visual inspection, and candidate selection algorithms that filter out non-slate frames in advance, reducing the computational burden on subsequent detailed analysis while maintaining comprehensive detection accuracy

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS7340096B2Method for identification of tokens in video sequences

Publication Date: 2008.03.04 INTERDIGITAL MADISON PATENT HLDG

AI summary

A method for identifying of tokens in a video sequence is described. First, the video sequence is scanned for boundaries between consecutive parts of the sequence where the appearance of the tokens is expected. After that step, candidate regions are pre-selected and classified in parts of the video sequence adjacent to detected boundaries, and tokens are located in the candidate regions. Information carried on the tokens is located, interpreted, and merged into consistent sets of information after passing a confidence analysis. In parallel a change in the visual appearance of a token, signaling a special event, is detected.