Polarization Sensor Positioning for Object Recognition Accuracy
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Solution Overview
Problem
The recognition rate of objects in real space, including estimating position, posture, and shape, is hindered by suboptimal information acquisition conditions, leading to decreased accuracy in object recognition.
Innovation Solution
An information processing system employing a depth sensor and polarization sensor to acquire depth information and polarization information, which are then used to guide the user in positioning the polarization sensor for improved reliability and accuracy of object recognition, utilizing augmented reality technology to superimpose virtual objects on real objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If polarization information is acquired under arbitrary acquisition conditions, then the information acquisition process is simple and fast, but the recognition accuracy and reliability of object recognition deteriorates
Solution Approach 1:
The system pre-calculates and stores optimal acquisition conditions (拍摄条件) for polarization information based on different object types and recognition scenarios. Before actual recognition, the system selects appropriate pre-established conditions rather than performing real-time optimization, thereby improving recognition accuracy while avoiding complex real-time computation.
Solution Approach 2:
The system adjusts polarization information acquisition parameters (such as polarization angles, exposure time, illumination intensity) based on the selected acquisition conditions. By changing these parameters according to pre-established condition sets, the system optimizes recognition accuracy for different scenarios without requiring complex adaptive algorithms.
2Reliability
If multiple polarization images are acquired under different conditions to improve recognition accuracy, then the recognition reliability improves, but the information acquisition time and processing complexity increases
Solution Approach 1:
The system pre-establishes multiple sets of acquisition conditions corresponding to different object characteristics and recognition requirements. When recognition is needed, the system directly applies these pre-prepared condition sets, avoiding the need to acquire all possible polarization images under all conditions, thus balancing reliability with time efficiency.
Solution Approach 2:
Instead of acquiring complete polarization information under all possible conditions, the system selectively acquires polarization images only under the specific pre-established conditions most relevant to the current recognition task. This partial action approach maintains sufficient recognition reliability while significantly reducing acquisition time.
3Measurement precision
If the polarization sensor is positioned arbitrarily, then the operation is simple and quick, but the quality and reliability of polarization information deteriorates
Solution Approach 1:
The system provides real-time feedback to the user regarding the current polarization sensor positioning quality. When the sensor is not in the optimal position according to the pre-established conditions, the system notifies the user and guides adjustment, ensuring high polarization information quality while maintaining ease of operation through intuitive feedback mechanisms.
Solution Approach 2:
The system automatically adjusts or selects the optimal polarization sensor positioning based on pre-established conditions and current recognition requirements, reducing the need for manual positioning operations. The system serves itself by autonomously determining and implementing the correct sensor orientation for each recognition task.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy of object recognition by optimizing the acquisition of polarization information, improving the reliability of the recognition process and resolving issues related to indefiniteness in polarization normals, thereby improving the overall recognition of objects in real space.
Implementation Method 1
a position, a posture, and a shape of an object in a real space on the basis of polarization information acquired by a polarization sensor
Implementation Method 2
depth information and polarization information acquired by a depth sensor and a polarization sensor, respectively
Data Source
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AI summary
It is possible to acquire information used for recognizing an object in a real space in a more suitable manner. An information processing apparatus includes: an estimating unit that estimates a normal on at least a part of a face of an object in a real space on the basis of polarization information corresponding to a detection result of each of a plurality of beams of polarized light acquired by a polarization sensor and having different polarization directions; and a control unit that controls output of notification information for guiding a change in a position in the real space according to an estimation result of the normal.