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1 /*M///////////////////////////////////////////////////////////////////////////////////////
2 //
3 //  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
4 //
5 //  By downloading, copying, installing or using the software you agree to this license.
6 //  If you do not agree to this license, do not download, install,
7 //  copy or use the software.
8 //
9 //
10 //                        Intel License Agreement
11 //                For Open Source Computer Vision Library
12 //
13 // Copyright (C) 2000, Intel Corporation, all rights reserved.
14 // Third party copyrights are property of their respective owners.
15 //
16 // Redistribution and use in source and binary forms, with or without modification,
17 // are permitted provided that the following conditions are met:
18 //
19 //   * Redistribution's of source code must retain the above copyright notice,
20 //     this list of conditions and the following disclaimer.
21 //
22 //   * Redistribution's in binary form must reproduce the above copyright notice,
23 //     this list of conditions and the following disclaimer in the documentation
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26 //   * The name of Intel Corporation may not be used to endorse or promote products
27 //     derived from this software without specific prior written permission.
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31 // warranties of merchantability and fitness for a particular purpose are disclaimed.
32 // In no event shall the Intel Corporation or contributors be liable for any direct,
33 // indirect, incidental, special, exemplary, or consequential damages
34 // (including, but not limited to, procurement of substitute goods or services;
35 // loss of use, data, or profits; or business interruption) however caused
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38 // the use of this software, even if advised of the possibility of such damage.
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40 //M*/
41 #include "_cv.h"
42 
43 /*F///////////////////////////////////////////////////////////////////////////////////////
44 //    Name:    cvCreateConDensation
45 //    Purpose: Creating CvConDensation structure and allocating memory for it
46 //    Context:
47 //    Parameters:
48 //      Kalman     - double pointer to CvConDensation structure
49 //      DP         - dimension of the dynamical vector
50 //      MP         - dimension of the measurement vector
51 //      SamplesNum - number of samples in sample set used in algorithm
52 //    Returns:
53 //    Notes:
54 //
55 //F*/
56 
cvCreateConDensation(int DP,int MP,int SamplesNum)57 CV_IMPL CvConDensation* cvCreateConDensation( int DP, int MP, int SamplesNum )
58 {
59     int i;
60     CvConDensation *CD = 0;
61 
62     CV_FUNCNAME( "cvCreateConDensation" );
63     __BEGIN__;
64 
65     if( DP < 0 || MP < 0 || SamplesNum < 0 )
66         CV_ERROR( CV_StsOutOfRange, "" );
67 
68     /* allocating memory for the structure */
69     CV_CALL( CD = (CvConDensation *) cvAlloc( sizeof( CvConDensation )));
70     /* setting structure params */
71     CD->SamplesNum = SamplesNum;
72     CD->DP = DP;
73     CD->MP = MP;
74     /* allocating memory for structure fields */
75     CV_CALL( CD->flSamples = (float **) cvAlloc( sizeof( float * ) * SamplesNum ));
76     CV_CALL( CD->flNewSamples = (float **) cvAlloc( sizeof( float * ) * SamplesNum ));
77     CV_CALL( CD->flSamples[0] = (float *) cvAlloc( sizeof( float ) * SamplesNum * DP ));
78     CV_CALL( CD->flNewSamples[0] = (float *) cvAlloc( sizeof( float ) * SamplesNum * DP ));
79 
80     /* setting pointers in pointer's arrays */
81     for( i = 1; i < SamplesNum; i++ )
82     {
83         CD->flSamples[i] = CD->flSamples[i - 1] + DP;
84         CD->flNewSamples[i] = CD->flNewSamples[i - 1] + DP;
85     }
86 
87     CV_CALL( CD->State = (float *) cvAlloc( sizeof( float ) * DP ));
88     CV_CALL( CD->DynamMatr = (float *) cvAlloc( sizeof( float ) * DP * DP ));
89     CV_CALL( CD->flConfidence = (float *) cvAlloc( sizeof( float ) * SamplesNum ));
90     CV_CALL( CD->flCumulative = (float *) cvAlloc( sizeof( float ) * SamplesNum ));
91 
92     CV_CALL( CD->RandS = (CvRandState *) cvAlloc( sizeof( CvRandState ) * DP ));
93     CV_CALL( CD->Temp = (float *) cvAlloc( sizeof( float ) * DP ));
94     CV_CALL( CD->RandomSample = (float *) cvAlloc( sizeof( float ) * DP ));
95 
96     /* Returning created structure */
97     __END__;
98 
99     return CD;
100 }
101 
102 /*F///////////////////////////////////////////////////////////////////////////////////////
103 //    Name:    cvReleaseConDensation
104 //    Purpose: Releases CvConDensation structure and frees memory allocated for it
105 //    Context:
106 //    Parameters:
107 //      Kalman     - double pointer to CvConDensation structure
108 //      DP         - dimension of the dynamical vector
109 //      MP         - dimension of the measurement vector
110 //      SamplesNum - number of samples in sample set used in algorithm
111 //    Returns:
112 //    Notes:
113 //
114 //F*/
115 CV_IMPL void
cvReleaseConDensation(CvConDensation ** ConDensation)116 cvReleaseConDensation( CvConDensation ** ConDensation )
117 {
118     CV_FUNCNAME( "cvReleaseConDensation" );
119     __BEGIN__;
120 
121     CvConDensation *CD = *ConDensation;
122 
123     if( !ConDensation )
124         CV_ERROR( CV_StsNullPtr, "" );
125 
126     if( !CD )
127         EXIT;
128 
129     /* freeing the memory */
130 	cvFree( &CD->State );
131     cvFree( &CD->DynamMatr);
132     cvFree( &CD->flConfidence );
133     cvFree( &CD->flCumulative );
134     cvFree( &CD->flSamples[0] );
135     cvFree( &CD->flNewSamples[0] );
136     cvFree( &CD->flSamples );
137     cvFree( &CD->flNewSamples );
138     cvFree( &CD->Temp );
139     cvFree( &CD->RandS );
140     cvFree( &CD->RandomSample );
141     /* release structure */
142     cvFree( ConDensation );
143 
144     __END__;
145 
146 }
147 
148 /*F///////////////////////////////////////////////////////////////////////////////////////
149 //    Name:    cvConDensUpdateByTime
150 //    Purpose: Performing Time Update routine for ConDensation algorithm
151 //    Context:
152 //    Parameters:
153 //      Kalman     - pointer to CvConDensation structure
154 //    Returns:
155 //    Notes:
156 //
157 //F*/
158 CV_IMPL void
cvConDensUpdateByTime(CvConDensation * ConDens)159 cvConDensUpdateByTime( CvConDensation * ConDens )
160 {
161     int i, j;
162     float Sum = 0;
163 
164     CV_FUNCNAME( "cvConDensUpdateByTime" );
165     __BEGIN__;
166 
167     if( !ConDens )
168         CV_ERROR( CV_StsNullPtr, "" );
169 
170     /* Sets Temp to Zero */
171     icvSetZero_32f( ConDens->Temp, ConDens->DP, 1 );
172 
173     /* Calculating the Mean */
174     for( i = 0; i < ConDens->SamplesNum; i++ )
175     {
176         icvScaleVector_32f( ConDens->flSamples[i], ConDens->State, ConDens->DP,
177                              ConDens->flConfidence[i] );
178         icvAddVector_32f( ConDens->Temp, ConDens->State, ConDens->Temp, ConDens->DP );
179         Sum += ConDens->flConfidence[i];
180         ConDens->flCumulative[i] = Sum;
181     }
182 
183     /* Taking the new vector from transformation of mean by dynamics matrix */
184 
185     icvScaleVector_32f( ConDens->Temp, ConDens->Temp, ConDens->DP, 1.f / Sum );
186     icvTransformVector_32f( ConDens->DynamMatr, ConDens->Temp, ConDens->State, ConDens->DP,
187                              ConDens->DP );
188     Sum = Sum / ConDens->SamplesNum;
189 
190     /* Updating the set of random samples */
191     for( i = 0; i < ConDens->SamplesNum; i++ )
192     {
193         j = 0;
194         while( (ConDens->flCumulative[j] <= (float) i * Sum)&&(j<ConDens->SamplesNum-1))
195         {
196             j++;
197         }
198         icvCopyVector_32f( ConDens->flSamples[j], ConDens->DP, ConDens->flNewSamples[i] );
199     }
200 
201     /* Adding the random-generated vector to every vector in sample set */
202     for( i = 0; i < ConDens->SamplesNum; i++ )
203     {
204         for( j = 0; j < ConDens->DP; j++ )
205         {
206             cvbRand( ConDens->RandS + j, ConDens->RandomSample + j, 1 );
207         }
208 
209         icvTransformVector_32f( ConDens->DynamMatr, ConDens->flNewSamples[i],
210                                  ConDens->flSamples[i], ConDens->DP, ConDens->DP );
211         icvAddVector_32f( ConDens->flSamples[i], ConDens->RandomSample, ConDens->flSamples[i],
212                            ConDens->DP );
213     }
214 
215     __END__;
216 }
217 
218 /*F///////////////////////////////////////////////////////////////////////////////////////
219 //    Name:    cvConDensInitSamplSet
220 //    Purpose: Performing Time Update routine for ConDensation algorithm
221 //    Context:
222 //    Parameters:
223 //    conDens     - pointer to CvConDensation structure
224 //    lowerBound  - vector of lower bounds used to random update of sample set
225 //    lowerBound  - vector of upper bounds used to random update of sample set
226 //    Returns:
227 //    Notes:
228 //
229 //F*/
230 
231 CV_IMPL void
cvConDensInitSampleSet(CvConDensation * conDens,CvMat * lowerBound,CvMat * upperBound)232 cvConDensInitSampleSet( CvConDensation * conDens, CvMat * lowerBound, CvMat * upperBound )
233 {
234     int i, j;
235     float *LBound;
236     float *UBound;
237     float Prob = 1.f / conDens->SamplesNum;
238 
239     CV_FUNCNAME( "cvConDensInitSampleSet" );
240     __BEGIN__;
241 
242     if( !conDens || !lowerBound || !upperBound )
243         CV_ERROR( CV_StsNullPtr, "" );
244 
245     if( CV_MAT_TYPE(lowerBound->type) != CV_32FC1 ||
246         !CV_ARE_TYPES_EQ(lowerBound,upperBound) )
247         CV_ERROR( CV_StsBadArg, "source  has not appropriate format" );
248 
249     if( (lowerBound->cols != 1) || (upperBound->cols != 1) )
250         CV_ERROR( CV_StsBadArg, "source  has not appropriate size" );
251 
252     if( (lowerBound->rows != conDens->DP) || (upperBound->rows != conDens->DP) )
253         CV_ERROR( CV_StsBadArg, "source  has not appropriate size" );
254 
255     LBound = lowerBound->data.fl;
256     UBound = upperBound->data.fl;
257     /* Initializing the structures to create initial Sample set */
258     for( i = 0; i < conDens->DP; i++ )
259     {
260         cvRandInit( &(conDens->RandS[i]),
261                     LBound[i],
262                     UBound[i],
263                     i );
264     }
265     /* Generating the samples */
266     for( j = 0; j < conDens->SamplesNum; j++ )
267     {
268         for( i = 0; i < conDens->DP; i++ )
269         {
270             cvbRand( conDens->RandS + i, conDens->flSamples[j] + i, 1 );
271         }
272         conDens->flConfidence[j] = Prob;
273     }
274     /* Reinitializes the structures to update samples randomly */
275     for( i = 0; i < conDens->DP; i++ )
276     {
277         cvRandInit( &(conDens->RandS[i]),
278                     (LBound[i] - UBound[i]) / 5,
279                     (UBound[i] - LBound[i]) / 5,
280                     i);
281     }
282 
283     __END__;
284 }
285