Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Vora, Ankit"'
This paper presents a novel approach for cross-view synthesis aimed at generating plausible ground-level images from corresponding satellite imagery or vice versa. We refer to these tasks as satellite-to-ground (Sat2Grd) and ground-to-satellite (Grd2
Externí odkaz:
http://arxiv.org/abs/2412.03315
The ground-to-satellite image matching/retrieval was initially proposed for city-scale ground camera localization. This work addresses the problem of improving camera pose accuracy by ground-to-satellite image matching after a coarse location and ori
Externí odkaz:
http://arxiv.org/abs/2409.06471
Mobile robots and autonomous vehicles are often required to function in environments where critical position estimates from sensors such as GPS become uncertain or unreliable. Single image visual place recognition (VPR) provides an alternative for lo
Externí odkaz:
http://arxiv.org/abs/2407.00863
Autor:
Zhang, Yanhao, Shi, Yujiao, Wang, Shan, Vora, Ankit, Perincherry, Akhil, Chen, Yongbo, Li, Hongdong
Vision-based localization for autonomous driving has been of great interest among researchers. When a pre-built 3D map is not available, the techniques of visual simultaneous localization and mapping (SLAM) are typically adopted. Due to error accumul
Externí odkaz:
http://arxiv.org/abs/2404.09169
Autor:
Ashokkumar, Thirumalaesh, Skinner, Katherine A, Agarwal, Siddarth, Vora, Ankit, Bhown, Ashutosh
Increasingly, autonomous vehicles (AVs) are becoming a reality, such as the Advanced Driver Assistance Systems (ADAS) in vehicles that assist drivers in driving and parking functions with vehicles today. The localization problem for AVs relies primar
Externí odkaz:
http://arxiv.org/abs/2403.05513
This paper proposes a fine-grained self-localization method for outdoor robotics that utilizes a flexible number of onboard cameras and readily accessible satellite images. The proposed method addresses limitations in existing cross-view localization
Externí odkaz:
http://arxiv.org/abs/2308.08110
Autor:
Kannapiran, Shenbagaraj, Bendapudi, Nalin, Yu, Ming-Yuan, Parikh, Devarth, Berman, Spring, Vora, Ankit, Pandey, Gaurav
Robust feature matching forms the backbone for most Visual Simultaneous Localization and Mapping (vSLAM), visual odometry, 3D reconstruction, and Structure from Motion (SfM) algorithms. However, recovering feature matches from texture-poor scenes is
Externí odkaz:
http://arxiv.org/abs/2308.01125
Image retrieval-based cross-view localization methods often lead to very coarse camera pose estimation, due to the limited sampling density of the database satellite images. In this paper, we propose a method to increase the accuracy of a ground came
Externí odkaz:
http://arxiv.org/abs/2307.08015
Autor:
Hausler, Stephen, Garg, Sourav, Chakravarty, Punarjay, Shrivastava, Shubham, Vora, Ankit, Milford, Michael
Can knowing where you are assist in perceiving objects in your surroundings, especially under adverse weather and lighting conditions? In this work we investigate whether a prior map can be leveraged to aid in the detection of dynamic objects in a sc
Externí odkaz:
http://arxiv.org/abs/2306.17536
Autor:
Hausler, Stephen, Garg, Sourav, Chakravarty, Punarjay, Shrivastava, Shubham, Vora, Ankit, Milford, Michael
Most 6-DoF localization and SLAM systems use static landmarks but ignore dynamic objects because they cannot be usefully incorporated into a typical pipeline. Where dynamic objects have been incorporated, typical approaches have attempted relatively
Externí odkaz:
http://arxiv.org/abs/2306.17529