In principle, the depth–velocity ambiguity can be overcome by independent assessments of depth (visually; e.g., from stereopsis) or ego-motion (e.g., from vestibular cues). Indeed, integration of visual and vestibular cues has been shown to play an important role both in the judgment of heading (e.g., Gu, Watkins, Angelaki, & DeAngelis,
2006) and in the estimation of traveled distance (Harris, Jenkin, & Zikovitz,
2000). Here, however, we focus on the possible contributions of visual cues. The classic approach to ego-motion detection from optic flow is based on the projection equation for moving patterns (Bruss & Horn,
1983; Koenderink & van Doorn,
1987; Longuet-Higgins & Prazdny,
1980) or the epipolar line constraint in discretized ego-motion models (Longuet-Higgins,
1981; for a review see Raudies & Neumann,
2012). In most algorithms, relative depth on the one hand and the ego-motion parameters of translation and rotation on the other are estimated in a joint process. Therefore, independent cues to environmental structure can be used to improve the result, as is indeed demonstrated in numerical simulations by Raudies and Neumann (
2012). Other algorithms, such as the local discontinuity approach by Rieger and Lawton (
1985), the subspace approaches by Heeger and Jepson (
1992) and Lappe and Rauschecker (
1994), or the template-matching algorithms by Franz, Chahl, and Krapp (
2004) and Perrone and Stone (
1994), compute heading and rotation independent of relative depth. As models of human ego-motion detection, these models predict that independent depth information should be of little help in ego-motion estimates.