海思IVE算法原理解析一--遮挡检测(occlusion deection)

前言

这个算法就是满足摄像头遮挡报警这个功能需求

代码分析

0xfffffffLL是个长整形，如果你也好奇这个写法的话。

流程

创建灰度图像的积分图计算任务
算出图像灰度值的平均值，均方差，u, v
再拿u,v计算不相似度。
不相似度>50%认为有遮挡
不相似度的计算标准：
输入图像灰度值的平均值 >80(为什么是写死的值？？？)，不相似度+1

代码

static HI_VOID* SAMPLE_IVE_OdProc(HI_VOID* pArgs)
{HI_S32 s32Ret;HI_U32 i, j;SAMPLE_IVE_OD_S* pstOd;VIDEO_FRAME_INFO_S stBaseFrmInfo;VIDEO_FRAME_INFO_S stExtFrmInfo;HI_S32 s32VpssGrp = 0;HI_S32 as32VpssChn[] = {VPSS_CHN0, VPSS_CHN1};HI_S32 s32MilliSec = 20000;IVE_DATA_S stSrc;IVE_DATA_S stDst;IVE_HANDLE IveHandle;HI_BOOL bFinish = HI_FALSE;HI_BOOL bBlock = HI_TRUE;HI_BOOL bInstant = HI_TRUE;POINT_S stChar[IVE_CHAR_NUM];POINT_S astPoints[10] = {{0, 0}};IVE_LINEAR_DATA_S stIveLinerData;HI_U64* pu64VirData = HI_NULL;IVE_DMA_CTRL_S stDmaCtrl = {IVE_DMA_MODE_DIRECT_COPY, 0, 0, 0, 0};HI_U64 u64TopLeft, u64TopRight, u64BtmLeft, u64BtmRight;HI_U64* pu64TopRow, *pu64BtmRow;HI_U64 u64BlockSum, u64BlockSq;HI_FLOAT fSqVar;HI_S32 s32VoLayer = 0;HI_S32 s32VoChn = 0;pstOd = (SAMPLE_IVE_OD_S*)(pArgs);pu64VirData = SAMPLE_COMM_IVE_CONVERT_64BIT_ADDR(HI_U64,pstOd->stInteg.au64VirAddr[0]);stIveLinerData.pstLinearPoint = &astPoints[0];stIveLinerData.s32LinearNum = 2;stIveLinerData.s32ThreshNum = IVE_CHAR_NUM / 2;stIveLinerData.pstLinearPoint[0].s32X = 80;stIveLinerData.pstLinearPoint[0].s32Y = 0;stIveLinerData.pstLinearPoint[1].s32X = 80;stIveLinerData.pstLinearPoint[1].s32Y = 20;while (HI_FALSE == s_bStopSignal){s32Ret = HI_MPI_VPSS_GetChnFrame(s32VpssGrp, as32VpssChn[1], &stExtFrmInfo, s32MilliSec);if(HI_SUCCESS != s32Ret){SAMPLE_PRT("Error(%#x),HI_MPI_VPSS_GetChnFrame failed, VPSS_GRP(%d), VPSS_CHN(%d)!\n",s32Ret,s32VpssGrp, as32VpssChn[1]);continue;}s32Ret = HI_MPI_VPSS_GetChnFrame(s32VpssGrp, as32VpssChn[0], &stBaseFrmInfo, s32MilliSec);SAMPLE_CHECK_EXPR_GOTO(HI_SUCCESS!=s32Ret, EXT_RELEASE,"Error(%#x),HI_MPI_VPSS_GetChnFrame failed, VPSS_GRP(%d), VPSS_CHN(%d)!\n",s32Ret,s32VpssGrp, as32VpssChn[0]);stSrc.u64VirAddr = stExtFrmInfo.stVFrame.u64VirAddr[0];stSrc.u64PhyAddr = stExtFrmInfo.stVFrame.u64PhyAddr[0];stSrc.u32Stride = stExtFrmInfo.stVFrame.u32Stride[0];stSrc.u32Width = stExtFrmInfo.stVFrame.u32Width;stSrc.u32Height = stExtFrmInfo.stVFrame.u32Height;stDst.u64VirAddr = pstOd->stSrc.au64VirAddr[0];stDst.u64PhyAddr = pstOd->stSrc.au64PhyAddr[0];stDst.u32Stride = stExtFrmInfo.stVFrame.u32Stride[0];stDst.u32Width =  stExtFrmInfo.stVFrame.u32Width;stDst.u32Height = stExtFrmInfo.stVFrame.u32Height;bInstant = HI_FALSE;s32Ret = HI_MPI_IVE_DMA(&IveHandle, &stSrc, &stDst, &stDmaCtrl, bInstant);SAMPLE_CHECK_EXPR_GOTO(HI_SUCCESS!=s32Ret, BASE_RELEASE,"Error(%#x),HI_MPI_IVE_DMA failed!\n", s32Ret);bInstant = HI_TRUE;//创建灰度图像的积分图计算任务s32Ret = HI_MPI_IVE_Integ(&IveHandle, &pstOd->stSrc, &pstOd->stInteg, &pstOd->stIntegCtrl, bInstant);SAMPLE_CHECK_EXPR_GOTO(HI_SUCCESS!=s32Ret, BASE_RELEASE,"Error(%#x),HI_MPI_IVE_Integ failed!\n", s32Ret);s32Ret = HI_MPI_IVE_Query(IveHandle, &bFinish, bBlock);while (HI_ERR_IVE_QUERY_TIMEOUT == s32Ret){usleep(100);s32Ret = HI_MPI_IVE_Query(IveHandle, &bFinish, bBlock);}SAMPLE_CHECK_EXPR_GOTO(HI_SUCCESS!=s32Ret, BASE_RELEASE,"Error(%#x),HI_MPI_IVE_Query failed!\n", s32Ret);//Tag :? IVE_CHAR_CALH = 8for (j = 0; j < IVE_CHAR_CALH; j++){pu64TopRow = (0 == j) ? (pu64VirData) : ( pu64VirData + (j * pstOd->u32H - 1) * pstOd->stInteg.au32Stride[0]);pu64BtmRow = pu64VirData + ((j + 1) * pstOd->u32H - 1) * pstOd->stInteg.au32Stride[0];for (i = 0; i < IVE_CHAR_CALW; i++){u64TopLeft  = (0 == j) ? (0) : ((0 == i) ? (0) : (pu64TopRow[i * pstOd->u32W - 1]));u64TopRight = (0 == j) ? (0) : (pu64TopRow[(i + 1) * pstOd->u32W - 1]);u64BtmLeft  = (0 == i) ? (0) : (pu64BtmRow[i * pstOd->u32W - 1]);u64BtmRight = pu64BtmRow[(i + 1) * pstOd->u32W - 1];//长长整形 LL   u64BlockSum = (u64TopLeft & 0xfffffffLL) + (u64BtmRight & 0xfffffffLL)- (u64BtmLeft & 0xfffffffLL) - (u64TopRight & 0xfffffffLL);u64BlockSq  = (u64TopLeft >> 28) + (u64BtmRight >> 28)- (u64BtmLeft >> 28) - (u64TopRight >> 28);// mean//stChar{s32X, s32Y} (u, sigmoid)stChar[j * IVE_CHAR_CALW + i].s32X = u64BlockSum / (pstOd->u32W * pstOd->u32H);// sigma=sqrt(1/(w*h)*sum((x(i,j)-mean)^2)= sqrt(sum(x(i,j)^2)/(w*h)-mean^2)fSqVar = u64BlockSq / (pstOd->u32W * pstOd->u32H) - stChar[j * IVE_CHAR_CALW + i].s32X * stChar[j * IVE_CHAR_CALW + i].s32X;stChar[j * IVE_CHAR_CALW + i].s32Y = (HI_U32)sqrt(fSqVar);}}// HI_S32 SAMPLE_IVE_Linear2DClassifer(POINT_S* pstChar, HI_S32 s32CharNum, \POINT_S* pstLinearPoint, HI_S32 s32Linearnum )//&stChar[0] addresss32Ret = SAMPLE_IVE_Linear2DClassifer(&stChar[0], IVE_CHAR_NUM,stIveLinerData.pstLinearPoint, stIveLinerData.s32LinearNum);//IVE_CHAR_NUM / 2 = 32if (s32Ret > stIveLinerData.s32ThreshNum){SAMPLE_PRT("\033[0;31m Occlusion detected!\033[0;39m\n");}s32Ret = HI_MPI_VO_SendFrame(s32VoLayer, s32VoChn, &stBaseFrmInfo,s32MilliSec);SAMPLE_CHECK_EXPR_GOTO(HI_SUCCESS!=s32Ret, BASE_RELEASE,"Error(%#x),SAMPLE_VO_SendFrame failed!\n", s32Ret);BASE_RELEASE:s32Ret = HI_MPI_VPSS_ReleaseChnFrame(s32VpssGrp,as32VpssChn[0], &stBaseFrmInfo);if (HI_SUCCESS != s32Ret){SAMPLE_PRT("Error(%#x),HI_MPI_VPSS_ReleaseChnFrame failed,Grp(%d) chn(%d)!\n",s32Ret,s32VpssGrp,as32VpssChn[0]);}EXT_RELEASE:s32Ret = HI_MPI_VPSS_ReleaseChnFrame(s32VpssGrp,as32VpssChn[1], &stExtFrmInfo);if (HI_SUCCESS != s32Ret){SAMPLE_PRT("Error(%#x),HI_MPI_VPSS_ReleaseChnFrame failed,Grp(%d) chn(%d)!\n",s32Ret,s32VpssGrp,as32VpssChn[1]);}}return HI_NULL;
}

总结

鸡肋，误判率应该挺高的
还不如像手机一样加传感器。
欢迎勘误。

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海思IVE算法原理解析一--遮挡检测(occlusion deection)

前言

代码分析

代码

总结

海思IVE算法原理解析一--遮挡检测(occlusion deection)相关推荐

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