Personalized Route Planning via Image Segmentation and Social Sharing
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Solution Overview
Problem
Current social media platforms lack effective methods for recommending and sharing customized multimedia route planning, which can enhance user interaction experiences by personalizing route recommendations based on user-specific interests and geographical locations.
Innovation Solution
A method and system that involves receiving a query image with an object-of-interest, performing integrative segmentation to determine contours, and using the MorphSnakes algorithm to find a route with maximum area overlap on a map, generating an output image, and sharing it on social networks, incorporating user interaction and Gaussian Mixture Models for accurate border identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional route planning methods are used, then route recommendations can be provided, but the personalization based on user interests and geographical locations is insufficient
Solution Approach 1:
The system segments the route planning process into multiple independent modules: image processing module for extracting objects from user photos, segmentation module for identifying specific regions, route recommendation module for generating personalized routes, and social media integration module for sharing. This modular segmentation enables personalized routing while keeping each module's complexity manageable and independent.
Solution Approach 2:
The patent introduces an intermediary image processing system that acts as a mediator between user inputs (photos, social media data) and the route planning algorithm. This intermediary layer processes and structures unstructured data into meaningful features that the routing system can utilize, enabling personalization without directly complicating the core routing logic.
2Measurement precision
If integrative segmentation process is performed to accurately identify object contours, then segmentation precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing images to identify and extract objects of interest before the actual route planning begins. The segmentation process identifies key features and contours in advance, creating a structured representation that can be quickly referenced during route generation, thus reducing real-time processing requirements while maintaining high accuracy.
Solution Approach 2:
The segmentation process employs dynamic algorithms that adapt their complexity based on the specific image characteristics and user requirements. The system dynamically adjusts segmentation granularity and processing depth, performing more detailed analysis only where necessary to achieve accurate contour detection, thereby optimizing the balance between precision and processing time.
3Adaptability or versatility
If multiple user specified information parameters are collected, then route personalization is enhanced, but information processing complexity increases
Solution Approach 1:
The system segments user-specified information into distinct categorical groups: geographical parameters (location, map ratio), object parameters (bounding box, contours), and preference parameters (expected route length, object-of-interest). Each segment is processed by specialized sub-routines that handle only relevant data types, reducing overall processing complexity while enabling comprehensive route customization through the integration of these segmented results.
Data Source
AI summary
In accordance with some embodiments of the disclosed subject matter, a method and a system for recommending and sharing customized multimedia route planning are provided. The method includes: receiving a query image from a user, the query image containing an object-of-interest of the user, performing an integrative segmentation process to determine one or more contours of the object-of-interest in the query image; determining a route having a maximum area overlap with the one or more contours of object-of-interest on a map image; generating an output image including the object-of-interest and the route; and recommending the output image to the user, and sharing the output image on a social network platform.