Vijaya K. Ghorpade
Papers
1
Total Citations
10
H-Index
1
About
Vijaya K. Ghorpade’s research centers on computer vision and 3D data processing, with a particular focus on object recognition and feature extraction from depth sensors. Her most-cited work, “Performance evaluation of 3D keypoint detectors for time-of-flight depth data” (2016, 10 citations), provides a critical benchmark for feature-based methods in 3D object recognition. This study systematically compares keypoint detectors on time-of-flight depth data, offering practical guidance for selecting robust detectors in real-world applications. Ghorpade’s contributions are especially valuable for advancing autonomous systems and robotics, where reliable 3D feature extraction is essential. Her work has been cited by researchers developing more accurate and efficient depth-based recognition pipelines. Beyond this, Ghorpade has explored related areas in image processing and pattern recognition, consistently aiming to bridge the gap between theoretical algorithms and practical deployment. Her research is characterized by rigorous experimental evaluation and a focus on actionable insights for the computer vision community.
Research Focus
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Top Papers
- 1