Insufficient memory in function cvAlloc, how to release memory?

edit

I have tried training my own classifier for a couple of times now (to detect cows) and just when I finally fine-tune my images in the positives data-set, I run into this while training:

I realize I have to release memory in order to free some space and referred to THIS

But I am actually a little confused as to how to proceed further. Can anyone help with an optimal solution for this so that I can resume my training? Thanks in advance.

Note:

1. my positives vary from 20-25KB on an average and negatives from 30-55KB.
2. Positives: 355x 280 pixels, I read somewhere that w,h must maintain this aspect ratio , hence used -w 71 -h 56
3. Im using 133 positives and 200 negatives, cows in positives all face the left side ( same profile)

EDIT::

text version:

PS E:\FYP\haar training\jo_haartrain> .\haartraining.exe -data cascades -vec vector/vector.vec -bg negative/bg.txt -n pos 67 -nneg 200 -nstages 12 -mem 2000 -mode ALL -w 64 -h 32

Data dir

name: cascades

Vec file name: vector/vector.vec

BG file name: negative/bg.txt

Num pos: 67

Num neg: 200

Num stages: 12

Num splits: 1 (stump as weak classifier)

Mem: 2000 MB

Symmetric: TRUE

Min hit rate: 0.995000

Max false alarm rate: 0.500000

Weight trimming: 0.950000

Equal weights: FALSE

Mode: ALL

Width: 64

Height: 32

Max num of precalculated features: 1309083

Applied boosting algorithm: GAB

Error (valid only for Discrete and Real AdaBoost): misclass

Max number of splits in tree cascade: 0

Min number of positive samples per cluster: 500

Required leaf false alarm rate: 0.000244141

Tree Classifier Stage

+---+ | 0| +---+

Number of features used : 1472939

Parent node: NULL

* 1 cluster *