Object recognition and localization with ultrasonic imaging in robotics applications

Kırağı, Hasan


KIRAGI, H; Ersak, Aydın (1994-04-14)
In this paper an object recognition and localization system based on ultrasonic range imaging to be used in optically opaque environments is introduced. The system is especially designed for robotics applications. The ultrasonic image is acquired by scanning ultrasonic transducers in two dimensions above the area where objects are located. The features that are used for recognition and localization processes are extracted from the outermost boundaries of the objects present in the input scene. Experimental ...
Object recognition and cognitive map formation using active stereo vision in a virtual world
Ulusoy, İlkay; Halıcı, Uğur (2003-01-01)
©2003 IEEE.In this paper we describe an algorithm for object recognition and cognitive map formation using stereo image data in a 3D virtual world where 3D objects and a robot with stereo imaging system are simulated. Stereo imaging system is simulated so that the actual human visual system properties such as focusing, accommodation, field of view are parameterized. Only the stereo images obtained from this world are supplied to the virtual robot (agent). By applying our disparity algorithm on stereo image ...
Object Detection for Autonomous Driving: High-Dynamic Range vs. Low-Dynamic Range Images
Kocdemir, Ismail H.; Akyüz, Ahmet Oğuz; Koz, Alper; Chalmers, Alan; Alatan, Abdullah Aydın; Kalkan, Sinan (2022-01-01)
© 2022 IEEE.An important problem in autonomous driving is to perceive objects even under challenging illumination conditions. Despite this problem, existing solutions use low-dynamic range (LDR) images for object detection for autonomous driving. In this paper, we provide a novel analysis on whether high-dynamic range (HDR) images can provide better performance for object detection for autonomous driving. To this end, we choose a seminal deep object detector and systematically evaluate its performance when ...
Object recognition and segmentation via shape models
Altınoklu, Metin Burak; Ulusoy, İlkay; Tarı, Zehra Sibel; Department of Electrical and Electronics Engineering (2016)
In this thesis, the problem of object detection, recognition and segmentation in computer vision is addressed with shape based methods. An efficient object detection method based on a sparse skeleton has been proposed. The proposed method is an improved chamfer template matching method for recognition of articulated objects. Using a probabilistic graphical model structure, shape variation is represented in a skeletal shape model, where nodes correspond to parts consisting of lines and edges correspond to pa...
Object tracking for surveillance applications using thermal and visible band video data fusion
Beyan, Çiğdem; Temizel, Alptekin; Department of Information Systems (2010)
Individual tracking of objects in the video such as people and the luggages they carry is important for surveillance applications as it would enable deduction of higher level information and timely detection of potential threats. However, this is a challenging problem and many studies in the literature track people and the belongings as a single object. In this thesis, we propose using thermal band video data in addition to the visible band video data for tracking people and their belongings separately for ...
Citation Formats
H. Kırağı, “Object recognition and localization with ultrasonic imaging in robotics applications,” Middle East Technical University, 1994.