Gm Global Technolgoy Operations, Inc.

Carnegie Mellon University

Industrial Technology Research Institute

Qi Wu

Wende Zhang

Tsuhan Chen

Vijayakumar Bhagavatula

Kai-Che Liu

Wen-Chao Chen

Fu-Chiang Jan

Cheng-Feng Wu

Tsu-Han Chen

A method for detecting a clear path of travel for a vehicle using a current image generated by a camera includes defining an exemplary vanishing point for each of a plurality of sample images. Features within each of the plurality of sample images are identified, the current image generated by the camera is monitored, and features within the current image are identified. The current image is matched to at least one of the sample images based upon the identified features within the current image and the identified features within the plurality of sample images. A vanishing point for the current image is determined based upon the matching and the exemplary vanishing point for each of the matched sample images. The vanishing point for the current image is utilized to define a clear path of travel, and the clear path of travel is utilized to navigate the vehicle.

Clear path detection using an example-based approach

A method for detecting a clear path of travel for a vehicle utilizing analysis of an image generated by a camera device located upon the vehicle includes monitoring the image, identifying through patch-based clear path detection analysis of the image a first patch within the image that indicates a not clear path, analyzing the first patch through patch smoothing, invalidating the first patch based upon the analyzing the first patch through patch smoothing, utilizing the invalidated first patch to define a clear path of travel for the vehicle, and utilizing the clear path of travel to navigate the vehicle.

Clear path detection with patch smoothing approach

A method for detecting a clear path of travel for a vehicle using a current image generated by a camera includes defining an exemplary clear path for each of a plurality of sample images, identifying features within each of the plurality of sample images, monitoring the current image generated by the camera, identifying features within the current image, matching the current image to at least one of the sample images based upon the identified features within the current image and the identified features within the plurality of sample images, determining a clear path of travel based upon the matching and the exemplary clear path for each of the matched sample images, and utilizing the clear path of travel to navigate the vehicle.

A method for detecting a clear path of travel for a vehicle utilizing an image generated by a camera device located upon the vehicle includes monitoring the image, and generating a plurality of patches onto the image, wherein the patches are collectively arranged to substantially include the clear path of travel. Feature extraction is utilized to analyze the patches and includes convolving each of the patches with a feature detection filter generating a feature-based filter response, extracting features based upon the feature-based filter response, and determining each of the patches to represent the clear path of travel or to not represent the clear path of travel based upon the extracted features. The clear path of travel is determined based upon the plurality of patches, and is utilized to navigate the vehicle.

Clear path detection using patch approach

A method for estimating a vanishing point in a roadway using a current image generated by a camera on a vehicle includes defining an exemplary vanishing point for each of a plurality of sample images, identifying features within each of the plurality of sample images, monitoring the current image generated by the camera, identifying features within the current image, matching the current image to at least one of the sample images based upon the identified features within the current image and the identified features within the plurality of sample images, determining a vanishing point based upon the matching and the exemplary vanishing points for each of the matched sample images, and utilizing the vanishing point to navigate the vehicle.

Clear path detection using a vanishing point

An example-based 2D to 3D image conversion method, a computer readable medium therefore, and a system are provided. The embodiments are based on an image database with depth information or with which depth information can be generated. With respect to a 2D image to be converted into 3D content, a matched background image is found from the database. In addition, graph-based segmentation and comparison techniques are employed to detect the foreground of the 2D image so that the relative depth map can be generated from the foreground and background information. Therefore, the 3D content can be provided with the 2D image plus the depth information. Thus, users can rapidly obtain the 3D content from the 2D image automatically and the rendering of the 3D content can be achieved.

Example-based two-dimensional to three-dimensional image conversion method, computer readable medium therefor, and system

A method is provided for removing an illumination generated shadow in a captured image. Each pixel of the captured input image is plotted on a two dimensional logarithmic graph. A linear axis for the plurality of color sets is determined that is substantially orthogonal to a respective illumination direction of each respective color set. A log-chromaticity value of each plotted pixel is projected on the axis. An orientation of the linear axis is selected to minimize an illumination effect and provide optimum separation between each of the respective color sets on the linear axis. Edges in the input image and illumination invariant image domain are identified. The identified edges of the input image are compared to identify edges in the illumination invariant image domain. A determination is made whether a shadow edge is present in response to the comparison. A shadow-reduced image is generated for scene analysis by a vehicle vision-based system.

Shadow removal in an image captured by a vehicle-based camera using an optimized oriented linear axis

A method is provided for removing an illumination generated shadow in a captured image. An image is captured by an image capture device. Each pixel of the captured image is represented by a respective color value in a logarithmic graph. A non-linear illumination-invariant kernel is determined. An illumination direction for each respective color set is determined in the logarithmic graph that is orthogonal to the non-linear illumination-invariant kernel. A log-chromaticity value of each plotted pixel is projected on the non-linear illumination-invariant kernel. Edges are identified in the input image. Edges are identified in the illumination-invariant image domain. The identified edges are compared. A determination is made whether a shadow is present in response to an edge identified in the input image and an absence of a correlating edge in the illumination-invariant image domain. A shadow-reduced image is generated for scene analysis by a vehicle vision-based system.

Shadow removal in an image captured by a vehicle based camera using a non-linear illumination-invariant kernel

A method for is provided for creating a shadow-reduced image from a captured image for distinguishing a clear path of travel. Each pixel of a captured input image is plotted according to a two dimensional logarithmic graph. A specific color set relating to an associated color value of a clear path. A linear illumination-invariant axis is determined as a function of the specific color set. An illumination direction for the linear illumination-invariant axis is determined. A log-chromaticity value of each plotted pixel of the specific color set is projected on the axis. Edges in the input image and the illumination-invariant image domain are identified. The identified edges of the input image are compared to identify edges in the illumination-invariant image domain. A determination is made whether a shadow edge is present in response to comparing the edges. A shadow-reduced image is generated for scene analysis by a vehicle vision-based system.

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Pittsburgh, PA, United States of America

Qi Wu