Dynamic Dictionary Switching for Stable Object Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing and capturing devices face challenges in stable object tracking when detecting multiple types of objects, as switching dictionary data every frame leads to missed detections and instability in object tracking due to limited arithmetic logic circuits and processing capacity.
Innovation Solution
An apparatus and method that utilize partial dictionary data for object detection in each frame and dynamically switch dictionary data based on detection results, prioritizing dictionary data for stable tracking and efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dictionary data is switched every frame to detect multiple object types, then detection versatility is improved, but object tracking stability deteriorates
Solution Approach 1:
The patent implements dynamic dictionary data switching based on detection history and object continuity. The system transitions from static per-frame dictionary selection to dynamic adaptation where dictionary data is retained or switched based on whether objects are detected in consecutive frames. This allows the system to maintain stable tracking for persistent objects while still detecting new object types when they appear, resolving the contradiction between tracking stability and detection versatility.
Solution Approach 2:
The patent ensures continuous object tracking by maintaining dictionary data across frames when objects are detected. The detection history accumulation mechanism preserves useful dictionary data that corresponds to detected objects, allowing continuous tracking without interruption. This continuity principle ensures that once an object is detected, it can be tracked across multiple frames even if the dictionary data would normally be switched, thereby maintaining tracking stability while preserving detection versatility.
2Measurement precision
If all dictionary data is processed for every frame to detect multiple object types, then detection accuracy is improved, but processing speed deteriorates
Solution Approach 1:
The patent extracts and processes only the necessary subset of dictionary data for each frame based on detection history. Instead of processing all dictionary data every frame, the system identifies and processes only those dictionary entries corresponding to detected objects or potential new objects. This extraction principle significantly reduces processing load while maintaining detection accuracy for relevant objects, resolving the contradiction between detection accuracy and processing speed.
Solution Approach 2:
The patent applies partial action by processing a selective portion of dictionary data rather than the complete set. The system processes dictionary data partially based on detection history, accumulating results only for relevant object types. This partial processing approach maintains sufficient detection accuracy for tracked and potential objects while dramatically reducing overall processing time and computational load, effectively resolving the accuracy-speed trade-off.
3Reliability
If dictionary data is retained across multiple frames for stable tracking, then object tracking stability is improved, but processing complexity increases
Solution Approach 1:
The patent implements self-service through automatic dictionary data management based on detection history. The system automatically determines which dictionary data to retain or switch without requiring complex external control mechanisms. The detection history accumulation and automatic switching logic enable the system to self-regulate dictionary data retention, maintaining tracking stability while minimizing processing complexity through automated decision-making rather than complex manual or external control systems.
Data Source
AI summary
An apparatus comprises a storage device configured to store a plurality of dictionary data for respectively detecting a plurality of different objects from an image; and at least one processor configured to function as: a detection unit configured to use partial dictionary data of the plurality of dictionary data to detect an object corresponding to the partial dictionary data, with respect to each frame of an image of a plurality of frames obtained by an image capturing device; and a switching unit configured to switch the dictionary data to be used by the detection unit in the plurality of frames, according to a result of the object detection by the detection unit.