Given k ≤ 6 points (x i , y i ) ∈ P 2 × P 2 , we characterize rank deficiency of the k × 9 matrix Z k with rows x i ⊗ y i in terms of the geometry of the point configurations {x i } and {y i }. While this question comes from computer vision the answer relies on tools from classical algebraic geometry: For k ≤ 5, the geometry of the rank-drop locus is characterized by cross-ratios and basic (projective) geometry of point configurations. For the case k = 6 the rank-drop locus is captured by the classical theory of cubic surfaces.