18205005. BEHAVIOR ESTIMATION DEVICE, BEHAVIOR ESTIMATION METHOD, AND RECORDING MEDIUM simplified abstract (NEC Corporation)

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BEHAVIOR ESTIMATION DEVICE, BEHAVIOR ESTIMATION METHOD, AND RECORDING MEDIUM

Organization Name

NEC Corporation

Inventor(s)

Ryuhei Ando of Tokyo (JP)

Yasunori Babazaki of Tokyo (JP)

BEHAVIOR ESTIMATION DEVICE, BEHAVIOR ESTIMATION METHOD, AND RECORDING MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 18205005 titled 'BEHAVIOR ESTIMATION DEVICE, BEHAVIOR ESTIMATION METHOD, AND RECORDING MEDIUM

Simplified Explanation

The abstract describes a behavior estimation device that extracts features from images to estimate a person's behavior. Here are the key points:

  • The device uses a person feature extraction means to extract features of a person detected from a series of images.
  • An object feature extraction means is used to extract features of an object detected from the same set of images.
  • A peripheral feature extraction means extracts features of the person's surroundings in the images.
  • A feature aggregation means combines the extracted features of the person, object, and surroundings.
  • A behavior estimation processing means then uses the aggregated features to estimate the person's behavior in the images.

Potential Applications

This technology has potential applications in various fields, including:

  • Surveillance systems: The behavior estimation device can be used to analyze and predict the behavior of individuals in surveillance footage, enhancing security and threat detection.
  • Retail analytics: By estimating customer behavior, the device can provide valuable insights for improving store layouts, product placement, and customer experience.
  • Human-computer interaction: The device can be integrated into interactive systems to understand and respond to user behavior, enabling more intuitive and personalized interactions.
  • Autonomous vehicles: By estimating the behavior of pedestrians and other objects in the environment, the device can enhance the decision-making capabilities of autonomous vehicles, improving safety and efficiency.

Problems Solved

The behavior estimation device addresses several problems:

  • Complex behavior analysis: By combining features of the person, object, and surroundings, the device can provide a more comprehensive understanding of behavior, overcoming the limitations of analyzing individual features in isolation.
  • Real-time estimation: The device can process a series of images in real-time, allowing for immediate behavior estimation and response.
  • Contextual understanding: By considering the person's surroundings, the device can better interpret behavior within its context, reducing false positives and improving accuracy.

Benefits

The use of this behavior estimation device offers several benefits:

  • Enhanced security: By accurately estimating behavior, the device can improve threat detection and prevent potential security breaches.
  • Improved efficiency: The device can automate the analysis of behavior, saving time and resources compared to manual observation and analysis.
  • Personalized experiences: By understanding individual behavior, the device can provide personalized recommendations and interactions, enhancing user experiences.
  • Safer autonomous systems: By estimating the behavior of pedestrians and objects, the device can help autonomous systems make safer and more informed decisions, reducing the risk of accidents.


Original Abstract Submitted

In the behavior estimation device, a person feature extraction means extracts a feature of a person detected from a plurality of images in a time series. An object feature extraction means extracts a feature of an object detected from the plurality of images. A peripheral feature extraction means extracts a feature of a periphery of the person in the plurality of images. A feature aggregation means executes aggregation processing for aggregating the feature of the person, the feature of the object, and the feature of the periphery of the person. A behavior estimation processing means executes estimation processing for estimating the person's behavior included in the plurality of images based on information including a processing result of the aggregation processing.

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