Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Singh, Chahat Deep"'
Autor:
Shah, Sachin, Rajyaguru, Naitri, Singh, Chahat Deep, Metzler, Christopher, Aloimonos, Yiannis
Publikováno v:
IEEE ROBOTICS AND AUTOMATION LETTERS, 2024
Autonomous robots often rely on monocular cameras for odometry estimation and navigation. However, the scale ambiguity problem presents a critical barrier to effective monocular visual odometry. In this paper, we present CodedVO, a novel monocular vi
Externí odkaz:
http://arxiv.org/abs/2407.18240
One of the core activities of an active observer involves moving to secure a "better" view of the scene, where the definition of "better" is task-dependent. This paper focuses on the task of human pose estimation from videos capturing a person's acti
Externí odkaz:
http://arxiv.org/abs/2407.01811
Autor:
Shah, Sachin, Chan, Matthew Albert, Cai, Haoming, Chen, Jingxi, Kulshrestha, Sakshum, Singh, Chahat Deep, Aloimonos, Yiannis, Metzler, Christopher
Point-spread-function (PSF) engineering is a well-established computational imaging technique that uses phase masks and other optical elements to embed extra information (e.g., depth) into the images captured by conventional CMOS image sensors. To da
Externí odkaz:
http://arxiv.org/abs/2406.09409
Autor:
He, Botao, Wang, Ze, Zhou, Yuan, Chen, Jingxi, Singh, Chahat Deep, Li, Haojia, Gao, Yuman, Shen, Shaojie, Wang, Kaiwei, Cao, Yanjun, Xu, Chao, Aloimonos, Yiannis, Gao, Fei, Fermuller, Cornelia
Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. These event cameras' output is dependent on both motion and texture. How
Externí odkaz:
http://arxiv.org/abs/2405.17769
Autor:
Shahidzadeh, Amir-Hossein, Yoo, Seong Jong, Mantripragada, Pavan, Singh, Chahat Deep, Fermüller, Cornelia, Aloimonos, Yiannis
Tactile exploration plays a crucial role in understanding object structures for fundamental robotics tasks such as grasping and manipulation. However, efficiently exploring such objects using tactile sensors is challenging, primarily due to the large
Externí odkaz:
http://arxiv.org/abs/2310.08745
Publikováno v:
Under review in ICRA 2023
In the era of deep learning, data is the critical determining factor in the performance of neural network models. Generating large datasets suffers from various difficulties such as scalability, cost efficiency and photorealism. To avoid expensive an
Externí odkaz:
http://arxiv.org/abs/2210.00715
Autor:
Singh, Chahat Deep, Sanket, Nitin J., Parameshwara, Chethan M., Fermüller, Cornelia, Aloimonos, Yiannis
Publikováno v:
IEEE International Conference on Robots and Systems (IROS) 2021
Recent advances in object segmentation have demonstrated that deep neural networks excel at object segmentation for specific classes in color and depth images. However, their performance is dictated by the number of classes and objects used for train
Externí odkaz:
http://arxiv.org/abs/2109.13859
Autor:
Sanket, Nitin J., Singh, Chahat Deep, Parameshwara, Chethan M., Fermüller, Cornelia, de Croon, Guido C. H. E., Aloimonos, Yiannis
The rapid rise of accessibility of unmanned aerial vehicles or drones pose a threat to general security and confidentiality. Most of the commercially available or custom-built drones are multi-rotors and are comprised of multiple propellers. Since th
Externí odkaz:
http://arxiv.org/abs/2106.15045
Autor:
Sanket, Nitin J., Singh, Chahat Deep, Asthana, Varun, Fermüller, Cornelia, Aloimonos, Yiannis
Morphable design and depth-based visual control are two upcoming trends leading to advancements in the field of quadrotor autonomy. Stereo-cameras have struck the perfect balance of weight and accuracy of depth estimation but suffer from the problem
Externí odkaz:
http://arxiv.org/abs/2011.03077
Odometry on aerial robots has to be of low latency and high robustness whilst also respecting the Size, Weight, Area and Power (SWAP) constraints as demanded by the size of the robot. A combination of visual sensors coupled with Inertial Measurement
Externí odkaz:
http://arxiv.org/abs/2006.06753