Market Context — Why This Technology, Why Now

Global industries are rapidly adopting automation and AI-driven solutions to enhance efficiency, safety, and productivity. This technology is critical for Industry 4.0 initiatives, where real-time, high-precision object tracking is essential for automated quality control, robotic guidance, and predictive maintenance. Furthermore, the escalating demand for advanced driver-assistance systems (ADAS) and smart city surveillance solutions underscores the immediate relevance and market potential for robust, adaptable tracking technologies.

Key Competitive Advantages
01

Achieves high-speed, high-precision tracking of fast-moving objects by combining low-frame-rate AI recognition with high-frame-rate template matching.

02

Adapts flexibly to environmental changes and temporary object occlusions by correcting ROI differences between the recognition start frame and the current frame, then re-initializing the tracking position.

03

Demonstrates strong technical uniqueness with only two prior art documents, offering licensees a significant advantage for early market share capture.

Market Opportunity
Smart Factory Automation
$0.5B–$1.5B globally (AI est.)
Demand is surging for this essential technology to automate manufacturing processes and improve quality, including defect detection, component tracking, and robotic arm coordination on production lines.
Industrial automation solution providers Manufacturing equipment OEMs Large-scale production facilities
Autonomous Driving & ADAS
$30B–$40B globally (AI est.)
Real-time tracking of vehicles, pedestrians, cyclists, and signs is critical for ensuring the safety and reliability of autonomous driving systems, driving intense technological competition.
Automotive Tier 1 suppliers Autonomous vehicle software developers Sensor and vision system manufacturers
Security & Surveillance Systems
$500M–$1B globally (AI est.)
High-precision automatic tracking is needed for widespread security, including suspicious person tracking, intrusion detection, and restricted area monitoring, especially amidst labor shortages.
Security system integrators Smart city solution providers Public safety technology developers
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

The patent covers a method, system, and program for object tracking, combining low-frame-rate AI recognition with high-frame-rate template matching, and includes a unique ROI difference correction and re-initialization step. It is considered robust, having successfully navigated an office action, indicating strong validity and scope.

Competitive White Space

This patent primarily focuses on software algorithms for object tracking. Licensees could build additional IP around specialized hardware acceleration for these algorithms, advanced multi-sensor fusion beyond visual data, or predictive analytics for object behavior.

Economic Impact
~$1.5M/year estimated operational cost reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

This technology could automate the tasks of 5 manual inspectors on an industrial inspection line. Assuming an annual personnel cost of ~$50K/inspector (AI est.), this could reduce annual labor costs by ~$175K (AI est.). Including reduced losses from missed defects, the total economic impact could reach ~$1.5M per year (AI est.).

Speed to Market
6× faster than in-house development
This technology combines established elements of learning-based recognition and template matching, enhanced by a unique difference correction and initialization logic for improved stability. This approach significantly reduces development time compared to building from scratch. Its high compatibility with existing image processing libraries and AI frameworks, primarily being a software implementation, facilitates rapid prototyping and deployment, accelerating time-to-market.
Competitive Positioning

X: High-Precision Recognition Efficiency
Y: High-Speed Tracking Stability

Business Models & Applications
📝 Licensing Model
By licensing this technology, companies can integrate it into their products or services for rapid market entry. Revenue can be generated through royalties or upfront fees.
💡 Solution Provision Model
Offer industry-specific packages (e.g., industrial inspection systems, smart city surveillance solutions) built around this technology, generating revenue from service fees and system integration costs.
🤝 Joint Development & Customization Model
Customize this technology to specific customer needs, jointly developing new solutions. Revenue can be generated through development fees and revenue sharing based on outcomes.
Adjacent Application Opportunities
🏭 スマートファクトリー
Automated Production Line Inspection & Quality Control
Applicable to real-time automatic tracking and detection of defects or foreign objects on high-speed moving products. This could ensure quality with precision and speed beyond human visual inspection, potentially improving production efficiency by an estimated 20-30%.
🚗 自動運転・モビリティ
Enhancing Safety for Next-Gen ADAS & Autonomous Driving
High-speed tracking of vehicles, pedestrians, cyclists, and obstacles improves the recognition accuracy and responsiveness of autonomous driving and advanced driver-assistance systems (ADAS). This could reduce accident risks by up to 15-20%, contributing to safer mobility.
🚁 ドローン・物流
Wide-Area Surveillance & Automated Drone Patrols
Automatically tracks suspicious individuals or vehicles at high speeds using drone-mounted camera footage across vast areas. This could enable efficient operations for infrastructure monitoring, security, and disaster assessment, potentially reducing manual patrol costs by ~40%.
Integration Roadmap — Estimated 8-Month Deployment
Phase 1: Requirements Definition & PoC
Duration: 2 months
Clarify specific challenges and goals for the adopting company and conduct a small-scale Proof of Concept to evaluate technology applicability. Define integration requirements with existing systems.
Phase 2: System Development & Integration
Duration: 4 months
Based on PoC results, develop and customize the technology for the adopting company's environment. Proceed with integration into existing image processing pipelines and surveillance systems.
Phase 3: Operational Testing & Go-Live
Duration: 2 months
Thoroughly test the developed system in a real environment to verify performance and stability. After final adjustments, initiate live operation and implement continuous improvements.
Technical Feasibility
This technology is centered on software-based algorithms combining learning-based recognition and template matching. The patent claims and detailed description indicate high compatibility with general-purpose image processing libraries and AI frameworks (e.g., OpenCV, TensorFlow, PyTorch). It can be implemented primarily through software updates or additions, leveraging existing camera systems and server infrastructure, thus offering technical feasibility with relatively easy adoption and reduced need for large-scale new equipment investment.
Success Scenario
Implementing this technology could automate high-speed object monitoring and inspection tasks traditionally performed manually. This would significantly reduce human error, improving product quality stability. Furthermore, 24/7 monitoring could increase production line operating rates by up to 20%, potentially expanding annual production volume by 1.2 times. Consequently, it is expected to simultaneously enhance labor productivity and reduce costs.
Patent Record
APPLICATION NO.
特願2020-553348
REGISTRATION NO.
7477168
FILING DATE
2019/10/18
GRANT DATE
2024/04/22
EXPIRATION DATE
2039/10/18
PATENT HOLDER
国立研究開発法人科学技術振興機構
Examination History
2022年09月15日
手続補正書（自発・内容）
2022年09月15日
出願審査請求書
2023年09月12日
拒絶理由通知書
2023年12月27日
手続補正書（自発・内容）
2023年12月27日
意見書
2024年03月19日
特許査定