Computer Vision Object Tracking With Click-Defined ROI Analytics
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Solution Overview
Problem
Conventional computer vision systems require coding expertise, lack tailored features for specific industries, and are less modular and flexible, limiting their performance and user interaction capabilities, especially in video-based analysis scenarios.
Innovation Solution
A system and method that allows users to define regions of interest and line crossings using mouse clicks and drags, converting these into coordinates for object tracking without coding, utilizing a Computer Vision model to generate analytics and adapt to specific industrial needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional computer vision systems use coding-based interfaces, then system functionality and processing capability are improved, but user accessibility and ease of operation deteriorate
Solution Approach 1:
The patent introduces a graphical user interface (GUI) as an intermediary layer between the user and the computer vision system. This GUI includes visual elements such as drag-and-drop interfaces, clickable buttons, and visual configuration options that allow users to interact with the system without needing to write code. The GUI translates user actions into system commands, maintaining full system functionality while dramatically improving accessibility for non-technical users.
2Stability of the object's composition
If conventional systems use monolithic architectures, then system stability is improved, but system flexibility and adaptability deteriorate
Solution Approach 1:
The patent implements a modular architecture where the computer vision system is divided into independent, interchangeable components. These modules can be selectively activated, configured, and arranged based on specific user needs. Each module handles a distinct function (e.g., object detection, tracking, analysis), allowing the system to be customized for different applications while maintaining overall stability through standardized module interfaces and communication protocols.
3Speed
If conventional systems focus on image-based processing, then processing speed is improved, but video-based analysis capability deteriorates
Solution Approach 1:
The patent applies preliminary processing techniques to video streams by extracting and processing individual frames sequentially. Before full video analysis, the system performs preliminary operations such as frame selection, key frame identification, and pre-processing on individual frames. This approach maintains the speed benefits of image-based processing while enabling comprehensive video analysis by processing frames in a streamlined manner and combining results across multiple frames.
Data Source
AI summary
Embodiments herein provide a method for detecting and tracking objects using a Computer Vision (CV) model. The method includes (i) receiving media content from a user device, (ii) rendering the media content into one or more frames with pre-defined dimensions, (iii) enabling a user to select one or more mouse points on at least one of the one or more frames to define a Region of Interest (ROI) and line crossings along with directions, (iv) converting the one or more mouse points into coordinates, (v) identifying coordinate details of the region of interest and the line crossings along with the directions, and (vi) tracking each object in the region of interest and the line crossings along with the directions based on the coordinate details and by assigning identification numbers to each object in the at least one of the one or more frames.