O/C

(redirected from Object Classification)
AcronymDefinition
O/COn Call
O/COfficer-in-Charge (US Navy)
O/COverclocking
O/COpen Circuit
O/COil on Canvas (painting style)
O/CObserver/Controller
O/COperational Command
O/COff-Centered
O/CObject Classification
O/CObserver/Collector
References in periodicals archive ?
PASCAL VOC dataset, which provides a standard evaluation system for detection algorithms and learning performance, is the most widely used standard dataset in the field of object classification and detection.
BoW-based methods have obtained remarkable results in recent years and they even obtained the best results for several classes in the recent PASCAL Visual Object Classes Challenge on object classification [8].
[18].Qi Zang, Reinhard Klette, "Object classification and tracking in video surveillance," Computer Analysis of Images and Patterns, vol.
For object classification, moment invariants (INVs) are often used as feature vector sets [9] for designing and applying machine learning technique.
Two additional sensors allow for object classification and live-wire detection.
Processing a video includes video segmentation, object detection, object classification and behavior analysis Honghai Liu et al.
The research of object classification uses database (first 12 elements of database are shown in TABLE I), which was also used by the authors [12].
(1) Through the analysis of texture, spectral, and geometrical features of surface subjects on DOM aerial photos of the study area, the image segmentation is expected to be made based on multiscale segmentation techniques, and the image objects are to be classified by object classification rule sets based mainly on spectral values, geometric characteristics, and spatial relationship between image and object so as to effectively extract the study gully.
Object classification is a difficult task as there usually exists large intraclass diversity and interclass correlation, even within a small image dataset.
“The See3CAM_10CUG is well suited for industrial applications such as object recognition/tracking on conveyors, 2d/3d barcode detection on moving objects and object classification. We also provide complete customization of the See3CAM series for any CMOS/CCD sensor, mechanical form-factor or interface such as HDMI/DVI/MIPI/DVP.
Experimental results show that the constructed affine invariant feature vector can be used for object classification.