# US 2019/0171889 A1 · Vehicle vision system with object detection > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0171889 A1 - Document ID: US20190171889A1 - Status: Published application - Kind: A1 - Application number: 16/266,180 - Filed: 2019-02-04 - Published: 2019-06-06 - Earliest claimed: 2015-07-30 - Assignees: Magna Electronics Inc. - Applicants: Magna Electronics Inc. - Inventors: Nikhil Gupta; Liang Zhang - Web page: https://patentgrep.com/patent/US20190171889A1 ## CPC - G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads - G06T 7/277: involving stochastic approaches, e.g. using Kalman filters - G06T 2207/30261: Obstacle - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract A vision system of a vehicle includes at least one camera disposed at a vehicle and having a field of view exterior of the vehicle, and an image processor operable to process image data captured by the camera. Responsive to image processing of captured image data, the image processor determines objects present in the field of view of the camera. The vision system processes additional frames of captured image data to enhance determination of objects of interest. The vision system initially detects an object present in the field of view of the camera and conducts hypotheses filtering and hypotheses merging and, responsive to the hypotheses merging, the system determines that the detected object is an object of interest or determines that the detected object is not an object of interest. ## Claims ### Claim 1 A vision system for a vehicle, said vision system comprising: at least one camera disposed at a vehicle and having a field of view exterior of the vehicle; wherein said camera comprises a pixelated imaging array having a plurality of photosensing elements; a control having an image processor that processes image data captured by said camera; wherein, responsive to processing by said image processor of captured image data, objects present in the field of view of said camera are detected; wherein, after detection via processing of captured image data by said image processor of at least one object present in the field of view of said camera, additional frames of captured image data are processed to discern the detected object being an object of interest from the detected object being not an object of interest; wherein said vision system utilizes hypotheses filtering and hypotheses merging to discern that the detected object is an object of interest; wherein hypotheses filtering comprises detecting the detected object in an initial frame of captured image data and tracking the detected object over multiple sets of frames of image data captured subsequent to the initial frame of captured image data; wherein hypotheses merging comprises comparing outputs of hypotheses filtering for multiple sets of frames of captured image data; and wherein, responsive to the results of hypotheses merging, said vision system determines that the detected object is an object of interest or determines that the detected object is not an object of interest. ### Claim 2 (depends on 1) The vision system of claim 1, wherein said vision system predicts hypotheses and evaluates predicted hypotheses to determine that the detected object is an object of interest or to determine that the detected object is not an object of interest. ### Claim 3 (depends on 2) The vision system of claim 2, wherein determination that the detected object is an object of interest by said vision system comprises hypotheses evaluation based at least in part on the predicted hypotheses. ### Claim 4 (depends on 1) The vision system of claim 1, wherein determination that the detected object is an object of interest by said vision system comprises hypotheses prediction based at least in part on the results of hypotheses merging. ### Claim 5 (depends on 4) The vision system of claim 4, wherein said vision system repeats the hypotheses merging and the hypotheses prediction to enhance determination that the detected object is an object of interest. ### Claim 6 (depends on 4) The vision system of claim 4, wherein filtered hypotheses and predicted hypotheses are combined to generate assigned hypotheses. ### Claim 7 (depends on 6) The vision system of claim 6, wherein the assigned hypotheses are input into a hypotheses prediction module, and wherein an output of the hypotheses prediction module is (i) input to hypotheses merging and (ii) input into a hypotheses evaluation module. ### Claim 8 (depends on 1) The vision system of claim 1, wherein, responsive to the results of hypotheses merging, said vision system determines that the detected object is a pedestrian and not an object not of interest. ### Claim 9 (depends on 8) The vision system of claim 8, wherein, responsive to the results of hypotheses merging, said vision system discerns the pedestrian from a tree. ### Claim 10 (depends on 1) The vision system of claim 1, wherein, responsive to the results of hypotheses merging, said vision system determines that the detected object is a bicycle and not an object not of interest. ### Claim 11 (depends on 10) The vision system of claim 10, wherein, responsive to the results of hypotheses merging, said vision system discerns the bicycle from a tree. ### Claim 12 (depends on 1) The vision system of claim 1, wherein hypotheses merging and hypotheses prediction comprises use of Kalman filtering. ### Claim 13 (depends on 1) The vision system of claim 1, wherein said camera comprises a fisheye lens. ### Claim 14 A vision system for a vehicle, said vision system comprising: at least one camera disposed at a vehicle and having a field of view exterior of the vehicle; wherein said camera comprises a pixelated imaging array having a plurality of photosensing elements; a control having an image processor that processes image data captured by said camera; wherein, responsive to processing by said image processor of captured image data, objects present in the field of view of said camera are detected; wherein, after detection via processing of captured image data by said image processor of at least one object present in the field of view of said camera, additional frames of captured image data are processed to discern the detected object being a pedestrian from the detected object being not a pedestrian; wherein said vision system utilizes hypotheses filtering and hypotheses merging to discern that the detected object is a pedestrian; wherein hypotheses filtering comprises detecting the detected object in an initial frame of captured image data and tracking the detected object over multiple sets of frames of image data captured subsequent to the initial frame of captured image data; wherein hypotheses merging comprises comparing outputs of hypotheses filtering for multiple sets of frames of captured image data; wherein hypotheses merging and hypotheses prediction comprises use of Kalman filtering; and wherein, responsive to the results of hypotheses merging, said vision system determines that the detected object is a pedestrian or determines that the detected object is not a pedestrian. ### Claim 15 (depends on 14) The vision system of claim 14, wherein, responsive to the results of hypotheses merging, said vision system discerns the pedestrian from a tree. ### Claim 16 (depends on 14) The vision system of claim 14, wherein determination that the detected object is a pedestrian by said vision system comprises hypotheses prediction based at least in part on the results of hypotheses merging, and wherein said vision system repeats the hypotheses merging and the hypotheses prediction to enhance determination that the detected object is a pedestrian. ### Claim 17 (depends on 16) The vision system of claim 16, wherein filtered hypotheses and predicted hypotheses are combined to generate assigned hypotheses, and wherein the assigned hypotheses are input into a hypotheses prediction module, and wherein an output of the hypotheses prediction module is (i) input to hypotheses merging and (ii) input into a hypotheses evaluation module. ### Claim 18 A vision system for a vehicle, said vision system comprising: at least one camera disposed at a vehicle and having a field of view exterior of the vehicle; wherein said camera comprises a pixelated imaging array having a plurality of photosensing elements; a control having an image processor that processes image data captured by said camera; wherein, responsive to processing by said image processor of captured image data, objects present in the field of view of said camera are detected; wherein, after detection via processing of captured image data by said image processor of at least one object present in the field of view of said camera, additional frames of captured image data are processed to discern the detected object being a bicycle from the detected object being not a bicycle; wherein said vision system utilizes hypotheses filtering and hypotheses merging to discern that the detected object is a bicycle; wherein hypotheses filtering comprises detecting the detected object in an initial frame of captured image data and tracking the detected object over multiple sets of frames of image data captured subsequent to the initial frame of captured image data; wherein hypotheses merging comprises comparing outputs of hypotheses filtering for multiple sets of frames of captured image data; wherein hypotheses merging and hypotheses prediction comprises use of Kalman filtering; and wherein, responsive to the results of hypotheses merging, said vision system determines that the detected object is a bicycle or determines that the detected object is not a bicycle. ### Claim 19 (depends on 18) The vision system of claim 18, wherein, responsive to the results of hypotheses merging, said vision system discerns the bicycle from a tree. ### Claim 20 (depends on 18) The vision system of claim 18, wherein determination that the detected object is a bicycle by said vision system comprises hypotheses prediction based at least in part on the results of hypotheses merging, and wherein said vision system repeats the hypotheses merging and the hypotheses prediction to enhance determination that the detected object is a bicycle. ### Claim 21 (depends on 20) The vision system of claim 20, wherein filtered hypotheses and predicted hypotheses are combined to generate assigned hypotheses, and wherein the assigned hypotheses are input into a hypotheses prediction module, and wherein an output of the hypotheses prediction module is (i) input to hypotheses merging and (ii) input into a hypotheses evaluation module.