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Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
Small object detection is a particular case of object detection where various techniques are employed to detect small objects in digital images and videos. "Small objects" are objects having a small pixel footprint in the input image. In areas such as aerial imagery, state-of-the-art object detection techniques under performed because of small ...
In computer vision, speeded up robust features (SURF) is a local feature detector and descriptor, with patented applications. It can be used for tasks such as object recognition, image registration, classification, or 3D reconstruction.
Multi-modal dataset for obstacle detection in agriculture including stereo camera, thermal camera, web camera, 360-degree camera, lidar, radar, and precise localization. Classes labelled geographically. >400 GB of data Images and 3D point clouds Classification, object detection, object localization 2017 [52] M. Kragh et al.
While video surveillance cameras proliferated with great adoption by users ranging from car dealerships and shopping plazas to schools and businesses to highly secured facilities such as nuclear plants, it was recognized in hindsight that video surveillance by human officers (also called "operators") was impractical and ineffective.
Video tracking is the process of locating a moving object (or multiple objects) over time using a camera. It has a variety of uses, some of which are: human-computer interaction, security and surveillance, video communication and compression, augmented reality, traffic control, medical imaging [1] and video editing.
Automatic target recognition (ATR) is the ability for an algorithm or device to recognize targets or other objects based on data obtained from sensors.. Target recognition was initially done by using an audible representation of the received signal, where a trained operator who would decipher that sound to classify the target illuminated by the radar.
Passive radar (also referred to as parasitic radar, passive coherent location, passive surveillance, and passive covert radar) is a class of radar systems that detect and track objects by processing reflections from non-cooperative sources of illumination in the environment, such as commercial broadcast and communications signals.