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Grouping fragmented contours into a (rough) shape

Objective: Track and classify person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to detect features (or classifier, HOG, etc)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

Grouping fragmented contours into a (rough) shape

Objective: Track and classify person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to detect features (or classifier, HOG, etc)etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

Grouping fragmented contours into a (rough) shape

Objective: Track and classify person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

Grouping fragmented contours into a (rough) shape

Objective: Track and classify person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

Grouping fragmented contours into a (rough) shape

Overall Objective: Track and classify person, dog, vehicle utilizing the Java bindings

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: Too many fragmented contours. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

Grouping fragmented contours into a (rough) shape

Overall Objective: Track and classify person, dog, vehicle utilizing the Java bindings

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: Too many fragmented contours. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

click to hide/show revision 7
Add ROIs as objective

Grouping fragmented contours into a (rough) shape

Overall Objective: Track and classify Create Regions of Interest (ROIs) in order to then examine them for objects such as person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: Too many fragmented contours. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

Grouping fragmented contours into a (rough) shapeRegion of Interest (ROI)

Overall Objective: Create Regions of Interest (ROIs) in order to then examine them for objects such as person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: Too many fragmented contours. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

click to hide/show revision 9
clarified the problem

Grouping Creating Regions of Interest (ROI) by clustering fragmented contours into a Region of Interest (ROI)contours

Overall Objective: Create Regions of Interest (ROIs) in order to then examine them for objects such as person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: Too many fragmented contours. contours for each object almost all the time. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

Creating Regions of Interest (ROI) by clustering fragmented contours

Overall Objective: Create Regions of Interest (ROIs) in order to then examine them for objects such as person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to encompassing smaller rect sent to classifier/etc

Problem: Too many fragmented contours for each object almost all the time. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

click to hide/show revision 11
better explanation of approach

Creating Regions of Interest (ROI) by clustering fragmented contours

Overall Objective: Create Regions of Interest (ROIs) in order to then examine them for objects such as person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to Region of Interest (smallest encompassing smaller rect rectangle around contours of an object) that is then sent to classifier/etcbe classified and/or recognized.

Problem: Too many fragmented contours for each object almost all the time. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

Creating Regions of Interest (ROI) by clustering fragmented contours

Overall Objective: Create Regions of Interest (ROIs) in order to then examine them for objects such as person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to Region of Interest (smallest encompassing rectangle around contours of an object) that is then sent to be classified and/or recognized.

Problem: Too many fragmented contours for each object almost all the time. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image

Creating Regions of Interest (ROI) by clustering fragmented contours

Overall Objective: Create Regions of Interest (ROIs) in order to then examine them for objects such as person, dog, vehicle utilizing the Java bindings

Approach: BackgroundSubtraction -> FindContours -> downselect to Region of Interest (smallest encompassing rectangle around contours of an object) that is then sent to be classified and/or recognized.

Problem: Too many fragmented contours for each object almost all the time. I've tried BackgroundSubtractorMOG and MOG2 with varying parameters (may not have tried the right combinations) along with erode/dilate and findContours(). The contours rarely completely enclose the subject, consisting instead of a number of contours that usually partially map to the subject. On top of that, there are sometime multiple objects (eg., person with dog) moving through the video stream. I am not able to reliable draw a rect around the full object in order to use that smaller window in which to detect features (or classifier, HOG, etc).

(I am addressing the shadow issue in a different thread)

My approach is leaning towards grouping contours that have some measure of nearness, though for people, the vertical elongation can be a complication for nearness calculations.

Question: Is there a method by which the nearness of contours can be evaluated, so as to group them into a larger contour/object?

Are there approaches to solving this problem? Below are images that illustrate the issue under consideration;

Contoured image

Original image

Silhouette image