A vehicle safety system includes several image capturing units, an image processing unit, a control unit and a display unit, in which an environmental photography technique and a visual distance detection technique are integrated so as to detect a distance between a nearby object and the vehicle to warn the driver during moving or parking operation, and an automatic door detection technique is integrated to identify rear side objects prior to opening of a vehicle door so to prevent undesired accident from happening.

Described is a robotic system for detecting obstacles reliably with their ranges by a combination of two-dimensional and three-dimensional sensing. In operation, the system receives an image from a monocular video and range depth data from a range sensor of a scene proximate a mobile platform. The image is segmented into multiple object regions of interest and time-to-contact (TTC) value are calculated by estimating motion field and operating on image intensities. A two-dimensional (2D) TTC map is then generated by estimating average TTC values over the multiple object regions of interest. A three-dimensional TTC map is then generated by fusing the range depth data with image. Finally, a range-fused TTC map is generated by averaging the 2D TTC map and the 3D TTC map.

A method and system for determining a distance and direction between a video camera secured on a vehicle and a target point relies on an electronic control unit. The system maps and stores grid points representing a world coordinate grid onto a screen coordinate grid and displays the video image on a display using the screen coordinate grid. The system obtains a target point of an object in the video image and determines a locus of four closest grid points of the screen coordinate grid that encircle the target point. The system determines screen distances from the target point to each of the four grid points and maps the four grid points onto the world coordinate grid. The electronic control unit interpolates the location of the target point in the world coordinate grid as weighted by the screen distances. Using the video camera location in world coordinates and the target point location in world coordinates, the system determines a distance between the video camera and the target point.

Provided are a collision avoidance method using a depth sensor, the method comprises receiving depth-based image information and identifying a path in the received depth-based image information, determining a depth level for each region of the depth-based image information, setting one or more distance-based sensing regions on the identified path based on the determined depth level, determining whether an object is detected in each of the set distance-based sensing regions and outputting a control signal for controlling the operation of a transport when determining that the object has been detected.

A multi-camera vision system for a vehicle includes a plurality of video cameras having respective fields of view external of the vehicle. Captured image data is provided to and processed at a central data processor in order to detect objects that are within the field of view of at least some of the video cameras. The vehicle is equipped with a sensor system having at least one non-visual sensor that senses sensor data in a region external of the vehicle. The sensed sensor data is provided to the central data processor. A potential hazard present exterior the vehicle is determined to exist via processing at the central data processor of at least one of received image data and received sensor data.

The present application provides an obstacle detection system and method thereof. The obstacle detection method comprises: obtaining a first image captured by a camera at a first time point; identifying a vertical edge candidate in the first image, and measuring a first length of the vertical edge candidate based on the first image; obtaining a second image captured by the camera at a second time point; measuring a second length of the vertical edge candidate based on the second image; calculating a difference between the first length and the second length; and comparing the difference with a predetermined length difference threshold, if the difference is greater than the length difference threshold, outputting a message that an obstacle is found.

The present invention provides a vehicle control method for driving safety, including: a first step of photographing an infrared image and a visible ray image; a second step of transmitting the photographed infrared image and visible ray image to an image recognizing and comparing module; a third step of leaving only a frequency for an edge of the infrared image and the visible image using a high pass filter, in the image recognizing and comparing module; and a fourth step of comparing a frequency band distribution processed in the third step to determine the situation as a situation which has a difficulty to secure a clear view when a difference is equal to or higher than a predetermined level.

The present invention relates to a freespace detection apparatus and method for identifying. A camera provides at least first and second image data captured at different points in time. Additionally, a motion vector of the camera is detected and assigned to the image data. The image data is transformed with respect to a predetermined, configurable image plane and motion compensation of the transformed image data is performed. Difference image data between the motion compensated transformed image data is computed and an object is identified in the computed difference image data.

In this way, an efficient and memory saving freespace detection can be realized. The freespace detection is scalable, and thus the freespace detection can be adapted to any available computational resources. The freespace detection can be applied to an Advanced Driver Assistance System or any other moving apparatus requiring a freespace detection.

In an object detection apparatus, a first trajectory estimation unit estimates a trajectory of a first object detected by an electromagnetic wave sensor. An optical flow acquisition unit image-processes a captured image acquired from a camera to acquire movement directions based on optical flows of feature points in the captured image. A movement direction match determination unit determines whether or not a match occurs between a movement direction based on the optical flows and a movement direction based on the trajectory of the first object. If a match occurs between the movement direction based on the optical flows of the plurality of feature points and the movement direction based on the trajectory of the first object, a sameness determination unit determines that a second object identified by the plurality of feature points and the first object are a same object.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.