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    <p>To obtain the bounding rectangle from a set of points, you can use the OpenCV <a href="http://docs.opencv.org/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html#boundingrect" rel="nofollow">boundingRect()</a> function. Also note the similar <a href="http://docs.opencv.org/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html#fitellipse" rel="nofollow">fitEllipse()</a> function.</p> <p><strong>boundingRect</strong><br> <em>Calculates the up-right bounding rectangle of a point set.</em></p> <pre><code>C++: Rect boundingRect(InputArray points) Python: cv2.boundingRect(points) → retval C: CvRect cvBoundingRect(CvArr* points, int update=0 ) Python: cv.BoundingRect(points, update=0) → CvRect </code></pre> <p>Parameters: points – Input 2D point set, stored in std::vector or Mat.<br> The function calculates and returns the minimal up-right bounding rectangle for the specified point set.</p> <p><strong>fitEllipse</strong><br> <em>Fits an ellipse around a set of 2D points.</em></p> <pre><code>C++: RotatedRect fitEllipse(InputArray points) Python: cv2.fitEllipse(points) → retval C: CvBox2D cvFitEllipse2(const CvArr* points) Python: cv.FitEllipse2(points) → Box2D </code></pre> <p>Parameters: points – Input 2D point set, stored in:</p> <pre><code>std::vector&lt;&gt; or Mat (C++ interface) CvSeq* or CvMat* (C interface) Nx2 numpy array (Python interface) </code></pre> <p>The function calculates the ellipse that fits (in a least-squares sense) a set of 2D points best of all. It returns the rotated rectangle in which the ellipse is inscribed. The algorithm [Fitzgibbon95] is used.</p>
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    1. POgrouping motion vectors
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    1. USChris
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    1. COyes you are right , I have already tried bounding rec, but now the problem is one object may contain more than one object. As you can see in the above output one car has several circles. Thank you any way.
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    2. COWhat is the desired output? Merging the overlapping objects? If you have one point describing each circle in your image (for example the centre) you could check if the distance between centres fell below some threshold (such as the current radius), if two circles are this close then you could define a new circle at their average position, expand the radius for the new point and remove the original points.
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    3. COthe desire output is to detect moving object. I also tried your idea, the problem is, if two or more car is close to each other then they merge all the circles together and shows as a single object
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