The conformal gravity fit to observed galactic rotation curves requires γ>0. On the other hand, the conventional method for light deflection by galaxies gives a negative contribution to the Schwarzschild value for γ>0, which is contrary to observation. Thus, it is very important that the contribution to bending should in principle be positive, no matter how small its magnitude is. Here we show that the Rindler-Ishak method gives a positive contribution to Schwarzschild deflection for γ>0, as desired. We also obtain the exact local coupling term derived earlier by Sereno. These results indicate that conformal gravity can potentially test well against all astrophysical observations to date

After the work of Rindler and Ishak, it is now well established that the bending of light is influenced by the cosmological constant Λ appearing in the Schwarzschild-de Sitter spacetime. We show that their method, when applied to the galactic halo gravity parametrized by a constant γ, yields exactly the same γ− correction to Schwarzschild bending as obtained by standard methods. Different cases are analyzed, which include some corrections to the special cases considered in the original paper by Rindler and Ishak.---------------------

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Motion trajectory contains plentiful motion information of moving objects, for example, human gestures and robot actions. Motion perception and recognition via trajectory are useful for characterizing them and a flexible descriptor of motion trajectory plays important role in motion analysis. However, in the existing tasks, trajectories were mostly used in raw data and effective descriptor is lacking. In this paper, we present a mixed invariant signature descriptor with global invariants for motion perception and recognition. The mixed signature is viewpoint invariant for local and global features. A reliable approximation of the mixed signature is proposed to reduce the noise in high-order derivatives. We use this descriptor for motion trajectory description and explore the motion perception with DTW algorithm for salient motion features. To achieve better accuracy, we modified the CDTW algorithm for trajectory matching in motion recognition. Furthermore, a controllable weight parameter is introduced to adjust the global features for tasks in different circumstances. The conducted experiments validated the proposed method.