Cv.LatentSvmDetectObjects Method (IplImage, CvLatentSvmDetector, CvMemStorage, Single)

CvLatentSvmDetectObjects Method (IplImage, CvLatentSvmDetector, CvMemStorage, Single)

OpenCvSharp Class Library

find rectangular regions in the given image that are likely to contain objects and corresponding confidence levels

Namespace: OpenCvSharp
Assembly: OpenCvSharp (in OpenCvSharp.dll) Version: 1.0.0.0 (1.0.0.0)

Syntax

public static CvSeq<CvObjectDetection> LatentSvmDetectObjects(
	IplImage image,
	CvLatentSvmDetector detector,
	CvMemStorage storage,
	float overlapThreshold
)

Public Shared Function LatentSvmDetectObjects ( 
	image As IplImage,
	detector As CvLatentSvmDetector,
	storage As CvMemStorage,
	overlapThreshold As Single
) As CvSeq(Of CvObjectDetection)

public:
static CvSeq<CvObjectDetection>^ LatentSvmDetectObjects(
	IplImage^ image, 
	CvLatentSvmDetector^ detector, 
	CvMemStorage^ storage, 
	float overlapThreshold
)

static member LatentSvmDetectObjects : 
        image : IplImage * 
        detector : CvLatentSvmDetector * 
        storage : CvMemStorage * 
        overlapThreshold : float32 -> CvSeq<CvObjectDetection>

Parameters

image: Type: OpenCvSharpIplImage
image to detect objects in
detector: Type: OpenCvSharpCvLatentSvmDetector
Latent SVM detector in internal representation
storage: Type: OpenCvSharpCvMemStorage
memory storage to store the resultant sequence of the object candidate rectangles
overlapThreshold: Type: SystemSingle
threshold for the non-maximum suppression algorithm = 0.5f [here will be the reference to original paper]

Return Value

Type: CvSeqCvObjectDetection

[Missing <returns> documentation for "M:OpenCvSharp.Cv.LatentSvmDetectObjects(OpenCvSharp.IplImage,OpenCvSharp.CvLatentSvmDetector,OpenCvSharp.CvMemStorage,System.Single)"]

Reference

Cv Class

LatentSvmDetectObjects Overload

OpenCvSharp Namespace