Papers
1
Total Citations
6
H-Index
1
About
Takashi Konno is a researcher in computer vision and robotics, with a primary focus on object detection and multi-view perception systems. His most cited work, "Incremental multi-view object detection from a moving camera" (2021, 6 citations), addresses the fundamental challenge of detecting objects in cluttered, occluded environments by leveraging temporal information from a moving camera. Konno’s key contribution is a novel method that incrementally accumulates detection scores across multiple frames, significantly improving robustness over single-image approaches. This work has practical implications for autonomous navigation, surveillance, and augmented reality, where reliable detection under challenging conditions is critical. While his citation count is modest, his research demonstrates a clear, applied focus on enhancing real-world vision systems through multi-frame integration. Konno’s approach stands out for its simplicity and effectiveness, offering a scalable solution for incremental object detection from mobile platforms.
Research Focus
Key Achievements
Top Papers
- 1Incremental multi-view object detection from a moving camera6 citations · 2021