Gesture Recognition Using Accumulated Probability Factors
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Solution Overview
Problem
Existing data processing devices for portable terminal devices often misjudge gesture operations due to subtle differences in motion, leading to erroneous judgments, where a flick operation may be mistaken for a tap operation and vice versa.
Innovation Solution
A data processing device with a detection section, a judging section, and a determining section that evaluates the processing status and attribute of the operation target to accurately determine the type of gesture operation, using pointers to evaluate the likelihood of tap or flick operations based on factors like ink remaining amount, contact duration, and image attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If gesture operation judgment is based merely on operation motion (physical operation status), then the judgment process is simple, but erroneous judgment occurs due to subtle differences in motion
Solution Approach 1:
The gesture judgment process is segmented into multiple independent evaluation dimensions: operation motion characteristics, processing status, and operation target attributes. Each dimension is evaluated separately to generate probability factors, which are then combined to determine the final gesture type. This segmentation allows the system to consider multiple aspects of the operation rather than relying solely on motion characteristics.
Solution Approach 2:
The system changes the parameters used for gesture judgment by introducing processing status parameters (such as whether the device is in a state where flick operations are expected) and operation target parameters (such as the type of object being operated on). These parameter changes enable the system to differentiate between gestures that have similar motions but different operational contexts, thereby improving judgment accuracy.
2Reliability
If multiple factors are considered for gesture determination, then judgment accuracy improves, but device complexity increases
Solution Approach 1:
The determination system dynamically adjusts the weight of different probability factors based on the current context. The weighting section assigns different weights to operation motion probability, processing status probability, and operation target probability depending on the situation. This dynamic weighting allows the system to adapt to different operational contexts without requiring a completely different determination mechanism for each case.
Solution Approach 2:
The system uses feedback from the processing status and operation target information to refine the gesture determination. The judgment results are used to update the understanding of the operational context, which in turn influences subsequent gesture judgments. This feedback mechanism allows the system to learn from previous operations and improve its determination accuracy over time.
Data Source
AI summary
The present invention is to appropriately determine a gesture operation detected to perform data processing according thereto. In the present invention, a CPU judges a processing status at the time of the detection of a gesture operation performed on a touch panel, and after determining its gesture operation type according to the processing status, performs data processing according to the operation type. In this case, the CPU determines and evaluates a gesture operation type for each processing status, and updates values (evaluation accumulation values) of a flick priority pointer and a tap priority pointer. Then, based on these values of the flick priority pointer and the tap priority pointer, the CPU determines one of the gesture operation types (flick operation/tap operation).