CloudTrack: Scalable UAV Tracking with Cloud Semantics
Nowadays, unmanned aerial vehicles (UAVs) are commonly used in search and rescue scenarios to gather information in the search area. The automatic identification of the person searched for in aerial footage could increase the autonomy of such systems, reduce the search time, and thus increase the missed person's chances of survival. In this paper, we present a novel approach to perform semantically conditioned open vocabulary object tracking that is specifically designed to cope with the limitations of UAV hardware. Our approach has several advantages. It can run with verbal descriptions of the missing person, e.g., the color of the shirt, it does not require dedicated training to execute the mission and can efficiently track a potentially moving person. Our experimental results demonstrate the versatility and efficacy of our approach.
Code (2)
Tasks
Object TrackingSimilar Papers 제목 키워드 기반
CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds
Clouds play a significant role in global temperature regulation through their effect on planetary albedo. Anthropogenic emissions of aerosols can alter the albedo of clouds, but the extent of this effect, and its consequ…
Instance SegmentationSegmentationSemantic SegmentationVisual Point Cloud Forecasting enables Scalable Autonomous Driving
In contrast to extensive studies on general vision, pre-training for scalable visual autonomous driving remains seldom explored. Visual autonomous driving applications require features encompassing semantics, 3D geometry…
3D geometryAutonomous DrivingMotion ForecastingFocusTrack: One-Stage Focus-and-Suppress Framework for 3D Point Cloud Object Tracking
In 3D point cloud object tracking, the motion-centric methods have emerged as a promising avenue due to its superior performance in modeling inter-frame motion. However, existing two-stage motion-based approaches suffer …
Object TrackingABCTracker: an easy-to-use, cloud-based application for tracking multiple objects
Visual multi-object tracking has the potential to accelerate many forms of quantitative analyses, especially in research communities investigating the motion, behavior, or social interactions within groups of animals. De…
Multi-Object TrackingObjectObject TrackingInterpreting Hidden Semantics in the Intermediate Layers of 3D Point Cloud Classification Neural Network
Although 3D point cloud classification neural network models have been widely used, the in-depth interpretation of the activation of the neurons and layers is still a challenge. We propose a novel approach, named Relevan…
3D Point Cloud ClassificationAdversarial AttackClassificationPoint Cloud Classification