Real-time multiview data fusion for object tracking with RGBD sensors
This paper presents a new approach to accurately track a moving vehicle with a multiview setup of red-green-blue depth (RGBD) cameras. We first propose a correction method to eliminate a shift, which occurs in depth sensors when they become worn. This issue could not be otherwise corrected with the ordinary calibration procedure. Next, we present a sensor-wise filtering system to correct for an unknown vehicle motion. A data fusion algorithm is then used to optimally merge the sensor-wise estimated trajectories. We implement most parts of our solution in the graphic processor. Hence, the whole system is able to operate at up to 25 frames per second with a configuration of five cameras. Test results show the accuracy we achieved and the robustness of our solution to overcome uncertainties in the measurements and the modelling.
Code (0)
등록된 구현이 없습니다.
Tasks
Object TrackingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
FROMAT: Multiview Material Appearance Transfer via Few-Shot Self-Attention Adaptation
Multiview diffusion models have rapidly emerged as a powerful tool for content creation with spatial consistency across viewpoints, offering rich visual realism without requiring explicit geometry and appearance represen…
MVD$^2$: Efficient Multiview 3D Reconstruction for Multiview Diffusion
As a promising 3D generation technique, multiview diffusion (MVD) has received a lot of attention due to its advantages in terms of generalizability, quality, and efficiency. By finetuning pretrained large image diffusio…
3D Generation3D ReconstructionMEAT: Multiview Diffusion Model for Human Generation on Megapixels with Mesh Attention
Multiview diffusion models have shown considerable success in image-to-3D generation for general objects. However, when applied to human data, existing methods have yet to deliver promising results, largely due to the ch…
3D GenerationImage to 3DNormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning
Multiview shape-from-shading (SfS) has achieved high-detail geometry, but its computation is expensive for solving a multiview registration and an ill-posed inverse rendering problem. Therefore, it has been mainly us…
Inverse RenderingEra3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention
In this paper, we introduce Era3D, a novel multiview diffusion method that generates high-resolution multiview images from a single-view image. Despite significant advancements in multiview generation, existing methods s…