Project: s41467-023-44554-8 | Function: Case3 (cpp)

system: You are an expert C++ programmer implementing algorithms from scientific papers.
Complete the masked function based on the algorithm description.
Follow C++ best practices and maintain consistent code style.
Return **only** the complete C++ function code.

user: Complete this C++ function:

**DESCRIPTION:** Implements Case 3 of the occlusion principle - detects objects moving along laser rays by checking if they recursively occlude themselves

**KEY TERMS:** {
  "p_spherical": "point in spherical coordinates",
  "cur_occ_times": "current occlusion times",
  "depth_map_list": "depth image library",
  "Case3IsOccluding": "check if point is occluding",
  "Case3DepthConsistencyCheck": "verify depth consistency",
  "occluding_times_thr3": "occlusion threshold for Case 3"
}

**CONTEXT CODE:**                             greater_num ++;
                        }
                    }
                }
            }
        }
    }
    if(all_num > 0)
    {
        if(num > 1)
        {           
            float cur_depth_thr = max(depth_cons_depth_thr2, k_depth2*p.vec(2));
            if(all_minus/(num-1) > cur_depth_thr)
            {
                return false;
            }      
        }
        if(greater_num == 0 || smaller_num == 0)
        {
            return true;
        }
        else
        {
            return false;
        }
    }
    else
    {
        return false;
    }  
}

bool  DynObjFilter::Case2VelCheck(float v1, float v2, double delta_t)
{   
    if(fabs(v1 - v2) < delta_t*acc_thr2)
    {
        return true;
    }
    return false;
}

bool  DynObjFilter::Case3VelCheck(float v1, float v2, double delta_t)
{
    if(fabs(v1 - v2) < delta_t*acc_thr3)
    {
        return true;
    }
    return false;
}

bool  DynObjFilter::Case3(point_soph & p)
{
  std::cerr << "Function Case3 has been masked" << std::endl;
  throw std::runtime_error("Function implementation has been masked");
}

bool  DynObjFilter::Case3Enter(point_soph & p, const DepthMap &map_info)
{
    if(p.dyn != STATIC)
    {
        return false;
    }
    float min_depth = 0;
    float depth_thr3_final = max(cutoff_value, k_depth_max_thr3*(p.vec(2) - d_depth_max_thr3)) + occ_depth_thr3;
    if(map_info.depth_map[p.position].size() > 0)
    {
        const point_soph* min_point = map_info.depth_map[p.position][map_info.min_depth_index_all[p.position]];
        min_depth = min_point->vec(2); 
        float delta_t = (p.time - min_point->time);
        depth_thr3_final = min(depth_thr3_final, v_min_thr3*delta_t);
    }
    if(dataset == 0 && p.is_distort)
    {
        depth_thr3_final = enlarge_distort*depth_thr3_final;
    }
    if(p.vec(2) < min_depth - depth_thr3_final)
    {
        case3_num ++;
        return true;
    }
    else
    {
        return false;
    }
}

bool  DynObjFilter::Case3MapConsistencyCheck(point_soph & p, const DepthMap &map_info, bool interp)
{
    float cur_v_min = v_min_thr3;
    float cur_hor = map_cons_hor_thr3;
    float cur_ver = map_cons_ver_thr3;
    float cur_depth = max(cutoff_value, k_depth_max_thr3*(p.vec(2) - d_depth_max_thr3)) + map_cons_depth_thr3;
    if(dataset == 0 && p.is_distort) cur_v_min = enlarge_distort*cur_v_min;
    for (int ind_hor = -map_cons_hor_num3; ind_hor <= map_cons_hor_num3; ind_hor ++)
    {
        for (int ind_ver = -map_cons_ver_num3; ind_ver <= map_cons_ver_num3; ind_ver ++)      
        {
            int pos_new = ((p.hor_ind + ind_hor)%MAX_1D) * MAX_1D_HALF + ((p.ver_ind +ind_ver)%MAX_1D_HALF);
            if (pos_new < 0 || pos_new >= MAX_2D_N)  continue;
            const vector<point_soph*> & points_in_pixel = map_info.depth_map[pos_new];                        
            if (map_info.max_depth_all[pos_new] > p.vec(2) + cur_depth && \
                map_info.min_depth_all[pos_new] < p.vec(2) - cur_depth)
            {
                continue;
            }   
            for (int j = 0; j < points_in_pixel.size(); j++)
            {
                const point_soph* point = points_in_pixel[j];
                if (point->dyn == STATIC && \
                    fabs(p.time-point->time) > frame_dur && \
                    (point->vec(2)-p.vec(2)) < cur_depth && \ 
                    fabs(p.vec(0)-point->vec(0)) < cur_hor && \
                    fabs(p.vec(1)-point->vec(1)) < cur_ver)
                {

                    return true;
                }               
            }         
        }
    }
    if(interp && (p.local(0) < self_x_b || p.local(0) > self_x_f || p.local(1) > self_y_l || p.local(1) < self_y_r))
    {
        float cur_interp = interp_thr3*(depth_map_list.back()->map_index - map_info.map_index + 1);
        float depth_all = DepthInterpolationAll(p, map_info.map_index, map_info.depth_map);
        if( fabs(p.vec(2) - depth_all)  < cur_interp) 
        {
            return true;
        }
        else
        {
            return false;
        }
    }
    return false;
}

bool  DynObjFilter::Case3SearchPointOccludedbyP(point_soph & p, const DepthMap &map_info)
{
    for (int ind_hor = -occ_hor_num3; ind_hor <= occ_hor_num3; ind_hor ++)
    {
        for (int ind_ver = -occ_ver_num3; ind_ver <= occ_ver_num3; ind_ver ++)
        {   
            int pos_new = ((p.hor_ind + ind_hor)%MAX_1D) * MAX_1D_HALF + ((p.ver_ind +ind_ver)%MAX_1D_HALF);                
            if (pos_new < 0 || pos_new >= MAX_2D_N)  continue;
            const vector<point_soph*> & points_in_pixel = map_info.depth_map[pos_new];            
            if (map_info.min_depth_all[pos_new] > p.vec(2))
            {
                continue;
            }   
            for (int j = 0; j < points_in_pixel.size(); j++)


Complete the function implementation replacing "throw std::runtime_error("Not implemented");".