Zobrazeno 1 - 10
of 7 511
pro vyhledávání: '"visual Tracking"'
Autor:
Guillermo A. Camacho-Muñoz, Sandra Esperanza Nope Rodríguez, Humberto Loaiza-Correa, João Paulo Silva do Monte Lima, Rafael Alves Roberto
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2024, Iss 1, Pp 1-32 (2024)
Abstract This paper addresses the problem of 6D pose tracking of plane segments from point clouds acquired from a mobile camera. This is motivated by manual packing operations, where an opportunity exists to enhance performance, aiding operators with
Externí odkaz:
https://doaj.org/article/0a25db1041bc4322be788ff09bef03a4
Publikováno v:
Systems Science & Control Engineering, Vol 12, Iss 1 (2024)
Most Siamese-based trackers adopt correlation operation to perform similarity matching on feature fusion of template branch and search branch. However, the correlation operation directly uses the template feature to slide the window on the search are
Externí odkaz:
https://doaj.org/article/3f985925f3dc4aef80daa23f6d43ea13
Publikováno v:
Hangkong bingqi, Vol 31, Iss 3, Pp 40-50 (2024)
Visual object tracking is a fundamental problem in computer vision. It has been widely used in civilian and military fields, such as battlefield reconnaissance, video surveillance, automatic driving, video analysis, and many other areas. In recent ye
Externí odkaz:
https://doaj.org/article/a70f213ecd2245858b6aca63da4a4322
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 3, Pp 3617-3632 (2024)
Abstract Convolutional neural networks (CNNs) have been the dominant architectures for feature extraction tasks, but CNNs do not look for and focus on some specific image features. Correlation operations play an important role in visual tracking. How
Externí odkaz:
https://doaj.org/article/ae5dbec3d6114a68b13ab3fcfaeefa79
Publikováno v:
IEEE Access, Vol 12, Pp 179981-179996 (2024)
With the aging of the population and the shortage of labor, the demand for service robots is increasing. As the key performance of visual tracking, it still has the problems of low tracking accuracy and poor real-time performance. Therefore, this pap
Externí odkaz:
https://doaj.org/article/f5514e4a50a94df99592dca5d5b4e12e
Publikováno v:
IEEE Access, Vol 12, Pp 177028-177037 (2024)
In this study, we introduce a probabilistic visual tracking method tailored for wild scenarios, where tracking environments experience abrupt changes over time. In probabilistic visual tracking, particularly when utilizing sequential Monte Carlo (MC)
Externí odkaz:
https://doaj.org/article/e2e5ef5b67de4c5db79c2543723469ad
Publikováno v:
IEEE Access, Vol 12, Pp 105662-105673 (2024)
Pan-Tilt Platform is essential for visually tracking moving targets over a wide range of regions. Due to the target’s unknown motion state and the tracking environment’s complexity, controlling the pan-tilt platform to keep the target at the cent
Externí odkaz:
https://doaj.org/article/1773373ee3fb47c082ccde7941dd5dc0
Publikováno v:
Computational Visual Media, Vol 10, Iss 2, Pp 193-214 (2024)
Abstract Visual object tracking has been drawing increasing attention in recent years, as a fundamental task in computer vision. To extend the range of tracking applications, researchers have been introducing information from multiple modalities to h
Externí odkaz:
https://doaj.org/article/e7d006b7cddf406686d821b2ef8ffbdd
Publikováno v:
IEEE Access, Vol 12, Pp 10172-10185 (2024)
Recently, Siamese-based trackers have emerged as the predominant focus in single object tracking research. However, the majority of these works concentrate on improving the backbone network of the tracker to enhance its performance, thereby overlooki
Externí odkaz:
https://doaj.org/article/c060545ccd8249f7a8f72ee4d8ba9f3b
Publikováno v:
Applied Sciences, Vol 14, Iss 20, p 9361 (2024)
To address the limitations of traditional footstep vibration signal localization algorithms, such as limited accuracy, single feature extraction, and cumbersome parameter adjustment, a motion target localization method for step vibration signals base
Externí odkaz:
https://doaj.org/article/df6df90d63ec4bf79d8a9a10a1322c75