The disclosure is directed to techniques for automatic segmentation of a region-of-interest (ROI) video object from a video sequence. ROI object segmentation enables selected ROI or “foreground” objects of a video sequence that may be of interest to a viewer to be extracted from non-ROI or “background” areas of the video sequence. Examples of a ROI object are a human face or a head and shoulder area of a human body. The disclosed techniques include a hybrid technique that combines ROI feature detection, region segmentation, and background subtraction. In this way, the disclosed techniques may provide accurate foreground object generation and low-complexity extraction of the foreground object from the video sequence. A ROI object segmentation system may implement the techniques described herein. In addition, ROI object segmentation may be useful in a wide range of multimedia applications that utilize video sequences, such as video telephony applications and video surveillance applications.

Multi-mode region-of-interest video object segmentation

The present invention involves a system for automatically screening closed circuit television (CCTV) cameras for large and small scale security systems, as used for example in parking garages. The system includes six primary software elements, each of which performs a unique function within the operation of the security system to provide intelligent camera selection for operators, resulting in a marked decrease of operator fatigue in a CCTV system. Real-time image analysis of video data is performed wherein a single pass of a video frame produces a terrain map which contains parameters indicating the content of the video. Based on the parameters of the terrain map, the system is able to make decisions about which camera an operator should view based on the presence and activity of vehicles and pedestrians, furthermore, discriminating vehicle traffic from pedestrian traffic. The system is compatible with existing CCTV (closed circuit television) systems and is comprised of modular elements to facilitate integration and upgrades.

System for automated screening of security cameras

A method for detecting a clear path of travel for a vehicle utilizing analysis of a plurality of images generated by a camera device located upon the vehicle includes monitoring the images. The images are analyzed including determining a clear path upon which a potential road surface can be estimated from other portions of the images that do not indicate a potential road surface, and determining an image of a traffic infrastructure indication. The method further includes determining the content of the traffic infrastructure indication, modifying the clear path based upon the content of the traffic infrastructure indication, and utilizing the modified clear path in navigation of the vehicle.

Enhanced clear path detection in the presence of traffic infrastructure indicator

A method for vehicle clear path detection using a camera includes imaging a ground area in front of the vehicle with the camera to produce a ground image and analyzing the ground image to formulate a clear path free of objects limiting travel of the vehicle.

Vehicle clear path detection

A system for determining a location of an object. The system includes an object location tracker and a computer system. The object location tracker is configured for attachment to a mobile vehicle and includes an object identification reading device and a position-tracking device. The object identification reading device senses object identification indicia on the object, such as RF ID tags, bar codes, etc., as the mobile vehicle moves around an environment in which the object is situated. The position-tracking device computes the location of the object location tracker as the mobile vehicle moves throughout environment. The computer system associates the sensed object identification indicia of the object, as determined by the reading device, with a location in the environment based on the position of the object location tracker in the environment, as determined by the position-tracking device, when the reading device senses the object identification indicia. The mobile vehicle may include its own mobility system, such as a forklift or an autonomous robotic device, or the mobile vehicle may be, for example, a pushcart that is pushed around the environment.

Systems and methods for determining a location of an object

A moving object is detected by subtraction between successive frames produced by a video camera and a position and a size of the moving object are determined. Preceding and succeeding frames produced by the video camera are stored into respective memories and the panning, tilting and zooming functions of the video camera are controlled according to the determined position and size of the moving object. A motion compensation is performed on the preceding frame to compensate for a motion of background image caused by a tracking movement of the camera so that coordinates of the motion-compensated frame are transformed to coordinates of the succeeding frame. An image difference between the motion-compensated frame and the succeeding frame is extracted as a moving object and a position and a size of the extracted image are determined, with which the video camera is adaptively controlled.

Method and system for tracking a fast moving object

PROBLEM TO BE SOLVED: To provide a mobile body tracking method and device therefor that can automatically track an intruding object moving at a high-speed with high accuracy by using one camera having a panning/tilt control function and a zoom control function. SOLUTION: The mobile body tracking device is provided with the camera 1 having a panning/tilt/zoom control function to automatically track a mobile body, an intruder detection means 3 that detects an intruder, a 1st image memory 4, a 2nd image memory 5, a mobile parameter calculation means 6, an inter-frame motion compensation means 7, a mobile body estimate means 8 and a camera control means 9.

Mobile body tracking method and device therefor

PURPOSE:To enable effective removing a background even when hierarchy compensation is difficult by inverse-Fourier transforming the Fourier component of a superposition picture from which the background component is removed and removing the background of the superposition picture CONSTITUTION:At first, the superposition picture 11 is Fourier-transformed by a Fourier transforming means and the Fourier transformation component 23 is stored in a Fourier component storage means 33 In the same way, the background picture 12 is Fourier-transformed by the Fourier transforming means 32 and the Fourier component 24 is stored in the Fourier component storage means 34 Next, the background component is removed by a background component removing means 35 with the Fourier component 23 of the superposition picture 11 and the Fourier component 26 of the background picture 12 is inputs so as to remove the background and the Fourier component 27 of the superposition picture 27 is stored in the Fourier component storage means 36 Then, inverse Fourier transformation is executed by an inverse Fourier transformation means 37 with the Fourier component 27 stored in the Fourier component storage means 36 as the input By the processing, a processing result 13 where the background component of the superposition picture is removed is obtained

Toshio Kamei

Papers

Method and system for tracking a fast moving object

Mobile body tracking method and device therefor

Method for removing background of superposition picture