Abstract: Systems and methods for multi-dimensional object detection are described. Embodiments disclose receiving image frames, extracting image components in the image frame, identifying line segments in the extracted components, grouping the line segments into groups, based at least in part on one or more similarities between the slope associated with a line segment and the spatial proximity between the line segments, and merging each of the one or more identified line segments in a selected group into a single line segment. Embodiments additionally disclose detecting the position of one or more objects in the image frame by identifying objects in the image frame, producing a second version of the image frame, applying at least one image classifier to the image frame and the second version of the image frame, and identifying coordinates associated with at least one target object. Some embodiments additionally couple lane and object detection with alert generation.

Abstract: A method and system for analyzing on-road traffic density are provided. The method involves allowing a user to select a video image capturing device and coordinates in a video image frame captured by the video image capturing device such that the coordinates form a region of interest (ROI). The ROI is processed to generate a confidence value and a traffic density value. The traffic density value is compared with a first set of threshold values. Based on the comparison, the traffic density values at different instants in a time window are displayed to enable monitoring of the traffic trend.

Abstract: A method and system for analyzing on-road traffic density are provided. The method involves allowing a user to select a video image capturing device and coordinates in a video image frame captured by the video image capturing device such that the coordinates form a region of interest (ROI). The ROI is processed to generate a confidence value and a traffic density value. The traffic density value is compared with a first set of threshold values. Based on the comparison, the traffic density values at different instants in a time window are displayed to enable monitoring of the traffic trend.