… surveillance systems in [13, 31, 36] which utilize common image information … -camera
scenario in this paper, and our main objective is to develop reliable and robust object detection …

… We apply erosion and dilation to the inverse distance transformed image edges. We
found that these morphologies smooth the objective function and improve the robustness to …

… by detecting independently moving objects in image sequence from a monocular camera …
to estimate a bound in the position of image pixel along the epipolar line. This is capable of …

… We first utilize the moving object detection results from the previous frame to re… image
according to road region detection results from the previous frame. The low-object and high-object …

… The accuracy of the region proposal network (R-CNN) together with its advanced versions,
SSD and YOLO v3 architectures, for object detection in aerial imaging has been studied. The …

… Object detection algorithms: While our work is applicable to object detection in general, we
focus … Assessing global detection accuracy: First, we denote the area on the image for each …

… 2017a)) and predict 3D objects with a lightweight camera 3D object detector. Given image
proposals and radar points, we associate image proposal with radar points by Soft Polar …

… camera fusion object detection method that combined image … of LiDAR–camera fusion
object detection methods is not high … ) for LiDAR–camera fusion 3D object detection. First, a 2D …

… detector that takes front view camera image and bird’s eye view LIDAR point cloud as
input and produces 3D bounding box from bird’s eye view without RoI pooling. The detection …

… the output of several object detectors applied at each viewpoint… Instead of predicting the
presence of an object at each image … lenging multi-camera pedestrian detection datasets namely …