Gesture Recognition via Segmented Trajectory Analysis
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Solution Overview
Problem
Existing gesture recognition methods require significant computing power, making them unsuitable for resource-constrained devices such as mobile devices in vehicle technology, where reliable and efficient gesture recognition is needed.
Innovation Solution
A method that captures image data from at least two individual images, segments the images to determine individual objects, calculates reference points, and tracks trajectories to identify gestures, using techniques like segmentation, trajectory analysis, and distance profiling to generate output signals without requiring extensive computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional gesture recognition methods are used, then recognition reliability is improved, but computing power requirements increase significantly
Solution Approach 1:
The patent segments the gesture recognition process into distinct phases: image acquisition, preprocessing, feature extraction, and gesture determination. By dividing the complex recognition task into smaller, manageable segments, the system achieves reliable gesture recognition while reducing overall computational burden on resource-constrained devices.
Solution Approach 2:
The patent performs preliminary actions by pre-processing images and extracting features before final gesture determination. Reference points are calculated in advance from segmented objects, and trajectories are pre-computed from sequences of reference points. This preliminary processing reduces the computational load during real-time gesture recognition.
2Measurement precision
If complex gesture analysis is performed, then gesture recognition accuracy is improved, but processing speed decreases
Solution Approach 1:
The patent extracts only the essential features needed for gesture recognition: reference points from segmented objects and trajectories from reference point sequences. By taking out and focusing on these critical elements rather than analyzing all image data, the system maintains high detection accuracy while achieving fast processing speeds suitable for real-time applications.
3Reliability
If comprehensive image processing is used, then gesture recognition reliability is improved, but device complexity increases
Solution Approach 1:
The patent applies local quality by performing segmentation and feature extraction only on relevant regions of the image data. Instead of processing entire images uniformly, the system focuses computational resources on detecting and analyzing specific objects and their trajectories, thereby achieving reliable gesture recognition with reduced system complexity.
Data Source
Figure 1~2A
Figure 2B~2C
Figure 3A~4B
AI summary
The invention relates to a method for detecting a user input on the basis of a gesture, in which method image data of at least two individual images are acquired, recoding times being allocated to the individual images. Each of the acquired individual images is segmented, an individual image object (31) is identified in each of the individual images and a reference point (33, 39) is determined on the basis of the individual image object (31). A trajectory (40) is determined on the basis of the reference points (33, 39) in the individual images and a gesture is determined on the basis of the trajectory (40). An output signal is generated and output on the basis of the gesture determined. The invention further relates to a device for detecting a user input on the basis of a gesture, comprising an acquisition unit (4) for acquiring image data, a segmentation unit (5) for performing segmentation, a trajectory computing unit (10) for determining the trajectory (40), an allocation unit (7) for determining a gesture and an output unit (8).