Stixel estimation methods and systems

1. A method for detecting an object, comprising:

receiving, by a processor, image data from an image sensor;

receiving, by the processor, radar data from a radar system;

processing, by the processor, the image data from the image sensor to determine one or more stixels;

processing, by the processor, the radar data from the radar system to determine one or more presence vectors;

fusing, by the processor, the one or more stixels and the one or more presence vectors using a deep learning method;

estimating, by the processor, a motion of the one or more stixels based on the fused stixels and presence vectors; and

detecting, by the processor, an object based on the estimated motion of the one or more stixels.

2. The method of claim 1 , wherein the processing comprises:

forming a region of interest (ROI) window of an image based on the image data; and moving the ROI window to a plurality of locations, from a left side of the image location to a right side of the image, to sequentially determine a presence of a stixel at each location.

3. The method of claim 1 , wherein the processing comprises:

forming a region of interest (ROI) window based on the image data;

determining whether a centerline of the ROI window includes a stixel using a convolution neural network; and

reporting a probability, a location, a height, and a class label when a stixel is determined.

4. The method of claim 1 , further comprising determining a velocity for each of the fused stixels and presence vectors, and wherein the detecting the object is based on the velocity of each of the fused stixels and presence vectors.

5. The method of claim 4 , further comprising determining a displacement for each of the fused stixels and presence vectors, and wherein the detecting the object is based on the displacement of each of the fused stixels and presence vectors.

6. A system for detecting an object, comprising:

an image sensor that generates image data;

a radar system that generates radar data; and

a computer module that, by a processor, processes the image data from the image sensor to determine one or more stixels, processes, the radar data from the radar system to determine one or more presence vectors, fuses the one or more stixels and the one or more presence vectors, estimates, a motion of the one or more stixels based on the fused stixels and presence vectors; and

and detects an object based on the estimated motion of the one or more stixels.

7. The system of claim 6 , wherein the computer module forms a region of interest (ROI) window of an image based on the image data; and moves the ROI window to a plurality of locations, from a left side of the image location to a right side of the image, to sequentially determine a presence of a stixel at each location.

8. The system of claim 6 , wherein the computer module forms a region of interest (ROI) window based on the image data, determines whether a centerline of the ROI window includes a stixel using a convolution neural network, and reports a probability, a location, a height, and a class label when a stixel is determined.

9. The system of claim 6 , wherein the computer module determines a velocity for each of the fused stixels and presence vectors, and detects the object based on the velocity of each of the fused stixels and presence vectors.

10. The system of claim 9 , wherein the computer module determines a displacement for each of the fused stixels and presence vectors, and detects the object based on the displacement of each of the fused stixels and presence vectors.

11. The system of claim 6 , wherein the image sensor and the radar system are associated with a vehicle, and wherein the control module detects the object in proximity to the vehicle.

12. The method of claim 1 , wherein the estimating the motion is based on an optimal column displacement in pixel using a standard dynamic programming minimization method.

13. The method of claim 12 , wherein the standard dynamic programming minimization method is a two-phase method with columns including locations of valid stixels of the one or more stixels and rows including motion.