11. A system to classify camera images, comprising a. means for generating a baseline gender model and an age estimation model using one or more convolutional neural networks (CNNs); b. means for capturing correspondences of faces by face tracking; c. means for applying a stochastic update rule for each face image determined as Ω - γ t ⁡ [ λ ⁡ ( Ω - Ω 0 ) + ( F ⁡ ( X t , Ω ) - y t ~ ) ⁢ ∂ ∂ Ω ⁢ F ⁡ ( X , θ ) ] , where y t ~ = 1  T ⁡ ( X t )  ⁢ ∑ Z ∈ T ⁡ ( X t ) ⁢ F ⁡ ( Z , Ω ) , γ t is the step size, term λ(Ω−Ω 0 ) represents weight decay, and a baseline neural network function is represented by y=F(X,Ω 0 ), and d. means for applying incremental learning to the CNNs and enforcing correspondence constraint such that CNN outputs are consistent and stable for one person.
18. The system of claim 11 , comprising means for performing multi-hypothesis visual tracking to obtain correspondence of faces in successive video frames.